About the Team:
We’re people that are passionate about making the internet a safer and more trusted place for all. We love the fraud and trust & safety space and want to teach companies how they can protect themselves, their users and create frictionless experiences for legitimate consumers. As a Forward Deployed Engineer, Trust and Safety, you are heavily experienced in detecting and acting on multiple types of online abuse from a technical and quantitative perspective. You’ve helped build tools, models and detection platforms at companies that have had to work through these threats at a global level.
What you’ll do:
Work with our Trust and Safety Architect and Data Science teams to surface emerging fraud patterns across the network escalate and proactively take them down.
Detect patterns and turn those findings into sharper signals, tighter configurations, and smarter decisioning logic.
Work across different verticals and closely with customers, partners and prospects with different risk appetites - some optimizing for approval rates, some minimizing chargebacks, some fighting account takeover and other types of abuse.
Help build dashboards, tune and build models, decision logic and custom signals to help customers achieve their desired business outcomes
Identify sources of false positives, possible coverage gaps and other vulnerabilities by digging into raw event streams; form a hypothesis, design a test and implement the fix
Lead forensic investigations during fraud spikes: trace attack patterns to their source, identify the technique being used, deliver a clear writeup with remediation steps
Distinguish between one-off anomalies and systemic gaps that indicate a product opportunity - and advocate for the latter with rigor
Contribute to detection frameworks, investigative tooling, and internal playbooks that make every engineer and analyst at Sift more effective
Be the conduit between customer reality and internal roadmap; your field observations should directly accelerate what Sift ships next
Some travel may be required
Required
5 - 8 years in fraud, trust & safety, risk, or a closely related data science domain - you've spent meaningful time working with fraud data, not just adjacent to it
Strong SQL and Python skills; you reach for code to answer a question, not to build a pipeline
Strong understanding of ML concepts applied to fraud: classification models, feature engineering, precision/recall tradeoffs, threshold calibration, score drift
Experience analyzing large-scale behavioral or transactional datasets to find patterns and anomalies - you know what a fraud ring looks like in the data, not just in a textbook
Ability to communicate technical findings to both technical and non-technical stakeholders; you can write a forensic investigation report and present it to a VP of Risk in the same week
Customer-facing experience; you understand that different businesses have different priorities, and that listening before optimizing is part of the job
Nice to Have
Hands-on experience with fraud detection platforms (in house or 3rd party)
Hands-on experience building with AI: LLM APIs, prompt engineering, or agentic workflows - whether that's automating an investigation step, building a tool that surfaces patterns from raw data, or wiring together a multi-step agent to accelerate fraud analysis
Familiarity with real-time event processing systems
Experience with rules-based decisioning systems alongside ML - knowing when a hard rule beats a model score
Background in payments, e-commerce, fintech, marketplace, or account security fraud
Prior forward deployed, staff engineering, or embedded consulting experience at a technical product company
Computer Science, Data Science, Mathematics, Statistics, Information Systems, Economics degree or equivalent
Let’s build it together:
At Sift, we are intentionally building a diverse, equitable, and inclusive workplace. We believe that diversity drives innovation, equity is a fundamental right, and inclusion is a basic human need. We envision a place where all Sifties feel secure sharing their authentic selves and diverse experiences with their teams, their customers, and their community – ultimately using this empowerment and authenticity to build trust and create a safer Internet.
This document provides transparency around how Sift handles the personal data of job applicants: https://sift.com/recruitment-privacy
A little about us:
Sift is the AI-powered fraud platform securing digital trust for leading global businesses. Our deep investments in machine learning and user identity, a data network scoring 1 trillion events per year, and a commitment to long-term customer success empower more than 700 customers to grow fearlessly. Global brands rely on Sift to unlock growth and deliver seamless consumer experiences. Visit us at sift.com and follow us on LinkedIn.
We’re hiring a Product and Customer Enablement Manager to own the strategy and delivery of learning experiences for two critical audiences: the internal teams who sell, implement, and support Sift’s products (Sales, Customer Success, Solutions, Support), and the customers who use them every day. This is a senior individual contributor role for someone who has built community and enablement programs from the ground up and is excited to do it again at a company where fraud, AI, and trust collide.
You’ll partner closely with Product, Product Marketing, Customer Success, and Sales leadership to identify capability gaps across personas, then design, build, and measure the programs that close them. You’re equally comfortable interviewing the product team about a new detection model, creating and facilitating a workshop for customer facing teams, managing an online customer community, and presenting adoption metrics to executives. You think in learning journeys, not one-off trainings — and you obsess over whether learners actually changed their behavior afterward.
If you’ve built enablement from scratch at a SaaS company, lived in an LMS, have experience in community management, and have strong opinions about what makes a great certification path, we want to talk to you.
• Lead Sift’s current internal and external enablement initiative: Own and operationalize a high-priority enablement program spanning both internal GTM teams and customers. Partner with CX, Product, Product Marketing, Sales, Support, and Solutions to turn fragmented product knowledge into structured learning paths, launch readiness motions, customer-facing education, and measurable adoption outcomes.
• Build learning journeys for multiple personas: Define and curate role-based learning paths for internal personas (AEs, SEs, CSMs, Solutions Consultants, Support) and external personas (customer admins, fraud analysts, integration engineers, executive sponsors), tailoring content depth, format, and cadence to each audience.
• Build and scale Sift’s customer education & community program: Develop the curriculum, certifications, and self-service learning library that helps customers ramp faster, expand their use of the platform, and achieve measurable outcomes — directly supporting retention and expansion goals. Manage the Sift customer community platform and content delivery.
• Design and develop content end-to-end: Apply instructional design best practices to produce engaging, outcomes-focused content and publish them to Sift’s LMS with reliable progress tracking, scoring, and reporting, and deliver content to customer community forums, and partner enablement platforms.
• Deliver high-impact training: Facilitate live and recorded training sessions for new hires, product launches, customer workshops, train-the-trainer sessions, and executive briefings — adapting style and depth to the audience.
• Support product enablement around launches: Partner with Product and Product Marketing to operationalize a repeatable launch enablement motion: readiness criteria, certification gates, sales plays, and customer facing assets shipped in lockstep with every major release.
• Define and track engagement and adoption metrics: Instrument programs with clear KPIs — completion rates, certification pass rates, time-to-productivity, content engagement, NPS/CSAT on training, and downstream impact on ramp, adoption, and revenue — and report on them in regular business reviews.
• Collaborate across stakeholders: Build durable relationships with internal SMEs (Product, Engineering, CS, Sales, Support, Trust & Safety) and external stakeholders (customers, partners, industry communities) to align enablement strategy with go-to-market priorities and customer outcomes.
• Champion a culture of continuous learning: Advocate for learning as a strategic lever — running needs assessments, capability mapping, and feedback loops that keep Sift’s enablement portfolio current as the product, market, and threat landscape evolve.
• 7+ years of experience in Learning & Development, Enablement, or Instructional Design, ideally including both internal (Sales/CS) enablement and external customer education at a B2B SaaS company.
• Proven track record of designing and launching multi-persona learning programs from scratch — not just maintaining existing curricula — and scaling them as the audience grows.
• Experience leading large-scale enablement initiatives across both employee and customer audiences, especially during periods of product change, GTM evolution, or customer experience transformation.
• Strong instructional design foundation with a portfolio of measurable program outcomes.
• Experience administering and optimizing LMS systems (e.g., Absorb, Lessonly, or similar), including reporting, integrations, and content governance.
• Demonstrated ability to define and track engagement and adoption metrics, and to tie learning outcomes to business results (ramp time, certification rates, product adoption, NPS, retention).
• Excellent facilitation and communication skills, comfortable leading live workshops, and producing polished written content.
• A self-starter who thrives in ambiguity, partners well cross-functionally, and can move fluidly between strategy and hands-on execution.
• Ability to translate strategy to operational execution, who is able to demonstrate initiative, perseverance, and grit in getting things done.
• Bachelor’s degree or equivalent practical experience; certifications such as ATD CPTD, CPLP, or instructional design credentials are a plus.
• Bonus: Experience in fraud prevention, risk, payments, identity, trust & safety, or another technical SaaS domain; experience building certification or partner enablement programs; multilingual content delivery.
• Introduction interview: 30-45 minutes with a recruiter to discuss your background, motivations, and the role.
• Hiring Manager screen: 60 minutes with the People leader to explore your enablement philosophy, experience, and fit for the role.
• Portfolio & craft deep dive: 60 minutes walking through samples of your work — a certification path, or a program you built end-to-end — including the design choices and measured outcomes.
• Virtual onsite loop with the team: approximately 3–4 hours covering: core role competencies & skills, cross-functional stakeholder partnership, metrics & program measurement, and values & behavior.
Let’s build it together:
At Sift, we are intentionally building a diverse, equitable, and inclusive workplace. We believe that diversity drives innovation, equity is a fundamental right, and inclusion is a basic human need. We envision a place where all Sifties feel secure sharing their authentic selves and diverse experiences with their teams, their customers, and their community – ultimately using this empowerment and authenticity to build trust and create a safer Internet.
This document provides transparency around how Sift handles the personal data of job applicants: https://sift.com/recruitment-privacy
A little about us:
Sift is the AI-powered fraud platform securing digital trust for leading global businesses. Our deep investments in machine learning and user identity, a data network scoring 1 trillion events per year, and a commitment to long-term customer success empower more than 700 customers to grow fearlessly. Global brands rely on Sift to unlock growth and deliver seamless consumer experiences. Visit us at sift.com and follow us on LinkedIn.
As a Machine Learning Engineer at Sift, you will bridge the gap between data science and large-scale distributed systems. You won’t just train models in isolation; you will build end-to-end pipelines that extract signals, train custom models per merchant, and serve predictions at production scale with low latency. You will work on an automated machine learning ecosystem that dynamically recalibrates models based on streaming global telemetry data.
Model Development & Refinement: Design, build, and deploy online machine learning models (including ensemble methods, deep learning, transformer architectures and graph-based models) to catch evolving fraud vectors in real time.
Feature Engineering at Scale: Engineer high-frequency time-series features from over 1 trillion behavioral events, optimizing for low-latency signal extraction and pattern recognition.
Production MLOps: Maintain and enhance our automated model training and deployment infrastructure, ensuring frictionless continuous integration and continuous deployment (CI/CD) of newly trained models.
System Optimization: Write high-performance code to minimize scoring latency at runtime, ensuring our core ML services scale seamlessly across distributed databases.
Collaborative Innovation: Work cross-functionally with Core Infrastructure, Product Management, and Data Science teams to translate business-level fraud patterns into robust algorithmic solutions.
Experience: 4+ years of professional experience building and deploying large-scale machine learning models into high-traffic production environments.
Solid Programming Foundations: Strong proficiency in Java or Scala (for our production backend) as well as Python (for data analysis and model prototyping).
Distributed Systems & Big Data: Practical experience with Databricks and big data processing frameworks like Apache Spark, Apache Flink, or Hadoop, and working with NoSQL data stores like Bigtable.
Strong Mathematical Foundations: Deep understanding of statistical modeling, probability, and standard machine learning algorithms (e.g., XGBoost, Random Forests, Neural Networks, and Clustering techniques).
System Design Mentality: Ability to reason through data consistency, pipeline failures, and performance constraints in a distributed, multi-tenant cloud environment (GCP).
Experience explicitly in the fraud detection, risk mitigation, or cyber-security domains.
Deep knowledge of streaming architectures (e.g., Apache Kafka).
Familiarity with containerization and orchestration tools like Docker and Kubernetes.
Familiarity with leveraging AI coding assistants (e.g., Claude Code) to accelerate development and model prototyping
Please note: final stage candidates may be asked to travel for in-person final round interviews.
Let’s build it together:
At Sift, we are intentionally building a diverse, equitable, and inclusive workplace. We believe that diversity drives innovation, equity is a fundamental right, and inclusion is a basic human need. We envision a place where all Sifties feel secure sharing their authentic selves and diverse experiences with their teams, their customers, and their community – ultimately using this empowerment and authenticity to build trust and create a safer Internet.
This document provides transparency around how Sift handles the personal data of job applicants: https://sift.com/recruitment-privacy
A little about us:
Sift is the AI-powered fraud platform securing digital trust for leading global businesses. Our deep investments in machine learning and user identity, a data network scoring 1 trillion events per year, and a commitment to long-term customer success empower more than 700 customers to grow fearlessly. Global brands rely on Sift to unlock growth and deliver seamless consumer experiences. Visit us at sift.com and follow us on LinkedIn.
About the team:
The Security Engineering team is responsible for protecting Sift’s products, infrastructure, and data while enabling our engineering organization to ship quickly and safely. We embed with product and platform teams, build and run security tooling, and design controls that scale across our cloud‑native environment. As a Senior Security Engineer, you’ll be a key technical contributor and subject‑matter expert, working on projects that materially reduce risk and strengthen Sift’s security posture.
Role:
In this role, you will design, implement, and operate security controls and tooling across Sift’s stack. You’ll work closely with Engineers, SREs, IT, and Legal/Compliance to secure our systems end‑to‑end—from application code and CI/CD pipelines to cloud infrastructure and identity. You will also help define our standards, mentor other engineers on secure practices, and contribute directly to audits and compliance efforts.
What you’ll do:
Design and implement security controls and tooling across Sift’s infrastructure and applications (e.g., IAM policies, network controls, secrets management, endpoint protections, container and workload security).
Embed with product and platform teams to perform security design reviews, threat modeling, and code or configuration reviews for new features and services.
Improve the secure SDLC by integrating AI-powered scanning tools, security scanning (SAST/DAST, dependency and container scanning) into CI/CD, and by developing guardrails, templates, and best practices for engineers.
Own or co‑own vulnerability management workflows, from discovery and triage through remediation, including defining SLAs, coordinating with service owners, and tracking closure.
Develop automation (scripts, services, integrations) to detect misconfigurations, anomalous activity, or policy violations, and to reduce manual operational work for the security team.
Participate in security incident response (on‑call rotation or escalation), including investigation, containment, root cause analysis, and long‑term fixes.
Contribute to security documentation and standards, ensuring we have clear, actionable guidance for engineers on topics like authentication, authorization, data encryption, and key management.
Support audits and assessments (e.g., SOC 2, customer security questionnaires) by providing technical details and evidence of control design and effectiveness.
Mentor other engineers on secure design and implementation practices through pairing, reviews, training sessions, and written guidance.
What will make you a strong fit:
5+ years of experience in security engineering, infrastructure engineering, or application security, ideally in a B2B SaaS or cloud‑native environment.
Hands‑on experience with at least one major public cloud platform (e.g., GCP, AWS), including IAM, networking, logging/monitoring, and security services.
Strong proficiency in at least one programming or scripting language (e.g., Python, Go, Java, or similar) and experience using code to automate security controls or detection.
Direct experience with AI/LLM-specific security risks (prompt injection, model supply chain, etc.)
Demonstrated knowledge of secure application and system design, including topics like authentication/authorization, encryption in transit and at rest, least‑privilege access, and secrets management.
Experience with security tooling such as vulnerability scanners, SAST/DAST tools, SIEM/centralized logging, endpoint protection, or cloud security posture management.
Solid understanding of common vulnerabilities and attack patterns (e.g., OWASP Top 10, misconfigurations, supply‑chain risks) and how to mitigate them in practice.
Ability to work cross‑functionally with engineering, IT, and compliance/legal teams, and to translate security requirements into practical implementation details.
Clear written and verbal communication skills, including the ability to document designs and decisions and to educate others on security best practices.
A collaborative, pragmatic approach: you’re comfortable making risk‑based decisions, proposing options, and supporting teams in implementing secure, scalable solutions.
Let’s build it together:
At Sift, we are intentionally building a diverse, equitable, and inclusive workplace. We believe that diversity drives innovation, equity is a fundamental right, and inclusion is a basic human need. We envision a place where all Sifties feel secure sharing their authentic selves and diverse experiences with their teams, their customers, and their community – ultimately using this empowerment and authenticity to build trust and create a safer Internet.
This document provides transparency around how Sift handles the personal data of job applicants: https://sift.com/recruitment-privacy
A little about us:
Sift is the AI-powered fraud platform securing digital trust for leading global businesses. Our deep investments in machine learning and user identity, a data network scoring 1 trillion events per year, and a commitment to long-term customer success empower more than 700 customers to grow fearlessly. Global brands rely on Sift to unlock growth and deliver seamless consumer experiences. Visit us at sift.com and follow us on LinkedIn.
at Sift (View all jobs)
Remote - East Coast US
About the Team:
At Sift, our mission is to help businesses thrive and trust their customers through our innovative fraud detection and prevention solutions. We are a committed team of professionals driving the fight against online fraud and abuse, fostering a safer digital world. Our collaborative and inclusive workplace is a hub for creativity and innovation.
Job Description:
We are seeking a customer-focused Professional Services Consultant with expertise in fraud prevention and risk management to help customers successfully implement, optimize, and scale our fraud solutions.
This role combines fraud strategy, technical implementation, and customer consulting. You will work directly with merchants, fintechs, financial institutions, i-gaming and digital businesses to design fraud prevention programmes, guide solution deployments, and ensure customers achieve measurable business outcomes.
The ideal candidate has either:
Experience implementing fraud prevention platforms at a leading fraud technology provider; or
Hands-on experience as a Fraud Analyst, Fraud Operations Manager, Risk Analyst, or Fraud Strategy Professional responsible for managing fraud programmes.
You will act as a trusted advisor throughout the customer lifecycle, helping organisations reduce fraud losses, improve approval rates, streamline operations, and build effective risk strategies.
Key Responsibilities:
Customer Implementation & Solution Delivery:
Lead customer onboarding and implementation projects from discovery through go-live.
Gather business, operational, and technical requirements to design effective fraud prevention solutions.
Configure and optimize fraud workflows, rules, decisioning logic, risk thresholds, and case management processes.
Partner with customer technical teams to support API integrations and deployment activities.
Develop implementation plans and success criteria aligned to customer objectives.
Fraud Strategy & Advisory:
Advise customers on fraud prevention best practices across payments, account takeover, onboarding, identity, abuse, and emerging fraud threats.
Analyse customer fraud trends, operational workflows, and performance metrics to identify optimisation opportunities.
Recommend strategies that balance fraud reduction, customer experience, operational efficiency, and revenue growth.
Conduct fraud strategy workshops and executive business reviews with key stakeholders.
Technical Consulting:
Serve as a subject matter expert on fraud detection technologies, risk decisioning, and platform capabilities.
Support customers in interpreting risk signals, model outputs, and fraud performance metrics.
Collaborate with Product, Engineering, Customer Success, and Support teams to resolve complex customer challenges.
Translate customer requirements into scalable solution designs and product feedback.
Training & Enablement
Deliver customer training and knowledge transfer sessions.
Create implementation documentation, best practice guides, and operational playbooks.
Enable customers to independently manage and optimise their fraud programmes.
Cross-Functional Collaboration
Partner closely with Sales, Customer Success, Product, Engineering, and Support teams to ensure successful customer outcomes.
Share customer insights and industry trends to influence product roadmap and innovation.
Contribute to internal best practices, implementation methodologies, and consulting frameworks.
Required Qualifications:
Bachelor's degree in Business, Information Technology, Computer Science, or a related field.
4–8+ years of experience in fraud prevention, fraud operations, risk management, professional services, solutions consulting, or a related field.
Experience implementing or managing fraud detection and prevention solutions.
Strong understanding of fraud typologies including payment fraud, account takeover, synthetic identity, onboarding fraud, promotion abuse, and policy abuse.
Experience working directly with customers or stakeholders in a consultative capacity.
Ability to translate business requirements into practical fraud solutions.
Strong analytical and problem-solving skills.
Excellent communication, presentation, and stakeholder management skills.
Familiarity with APIs, JSON, web technologies, and SaaS implementation methodologies.
Travel up to 30%.
Ability to work flexible hours to provide coverage to West Coast & European customers.
Preferred Qualifications:
Experience working at a fraud technology provider such as Sift, Forter, SEON, Riskified, Feedzai, Sardine, or similar organisations.
Previous experience as a Fraud Analyst, Fraud Operations Manager, Risk Manager, or Fraud Strategy Lead.
Experience supporting e-commerce, fintech, payments, marketplaces, gaming, banking, or digital platforms.
Knowledge of machine learning-based fraud detection, risk scoring, and decisioning systems.
Experience managing multiple customer implementations simultaneously.
Project management certification or equivalent experience.
Success in This Role:
Within your first year, you will:
Successfully deliver customer implementations and migrations.
Become a trusted advisor for fraud strategy and solution optimisation.
Help customers reduce fraud losses while maintaining strong customer experience and approval rates.
Contribute to implementation best practices that improve customer outcomes and time-to-value.
Let’s build it together:
At Sift, we are intentionally building a diverse, equitable, and inclusive workplace. We believe that diversity drives innovation, equity is a fundamental right, and inclusion is a basic human need. We envision a place where all Sifties feel secure sharing their authentic selves and diverse experiences with their teams, their customers, and their community – ultimately using this empowerment and authenticity to build trust and create a safer Internet.
This document provides transparency around how Sift handles the personal data of job applicants: https://sift.com/recruitment-privacy
A little about us:
Sift is the AI-powered fraud platform securing digital trust for leading global businesses. Our deep investments in machine learning and user identity, a data network scoring 1 trillion events per year, and a commitment to long-term customer success empower more than 700 customers to grow fearlessly. Global brands rely on Sift to unlock growth and deliver seamless consumer experiences. Visit us at sift.com and follow us on LinkedIn.
You will be joining Atlas, our Continuous Engineering team. Our focus is keeping existing customers successful: we take the feature requests and bug fixes that come through Customer Success and Product, prioritize them, and see them through to release. Because those requests can touch almost any part of the product, our work spans most of Sift’s major technical domains and products.
The requests we take on are typically high-impact and come directly from customers, so the work you do reaches production quickly. We have already delivered a wide range of customer-requested improvements, with many more planned.
This is a genuinely full-stack role. Depending on current priorities, you may spend some periods working primarily on the backend and others primarily on the frontend, and many features involve both. We are looking for someone who can own a problem end to end, wherever it leads.
BE Technical stack: Ruby, Ruby on Rails, Java, Dropwizard, GCP, Kubernetes, Kafka, BigTable, Spanner Graph DB, Postgres, Redis, gRPC, Python, Apache Airflow, Snowflake, BigQuery
FE Technical stack: ReactJS, React, React Query, React Router, Cypress, Jest, Storybook, SCSS
Prior experience with our specific backend stack is not required; backend experience in any language is sufficient, provided you are willing to work in ours. Hands-on experience with React, however, is expected.
Build and deliver customer-facing features end to end, across both the frontend and the backend. Some features are primarily one or the other; many involve both.
Work closely with Customer Success and Product to turn customer requests and bug reports into delivered features.
Work across different areas of our various product and technology areas, including Payments, Account Takeover, Dispute Management, Console, Workflows, and the API. You are not expected to know every area from the start; getting up to speed quickly is part of the role.
Contribute to backend services in our stack (Ruby on Rails, Java, and others), building your familiarity with it over time.
Help maintain our tooling and engineering practices so the team can continue to deliver reliably.
Experience: you will gain exposure across a broad range of Sift’s products, which few roles offer.
Professional growth: we run Growth Cycles rather than standard performance reviews, and the role is a strong opportunity to deepen your backend skills alongside your frontend experience.
Knowledge sharing: we hold regular Tech Talks, where you will learn how Sift handles data at very large scale.
Culture of innovation: you can put your own ideas into practice at our bi-annual Hackathon.
3+ years building React applications (React, React Query, React Router), along with familiarity with common testing tools such as Jest and Cypress.
At least one year of backend experience in any language. Specific experience with Ruby on Rails or Java is not required, but a willingness to work with them is.
A focus on customers and on delivering results, not only on writing code.
Comfort moving between different products and codebases.
Strong communication skills and a collaborative, team-first approach.
A degree in Computer Science, or equivalent experience.
This role is open to both junior and mid-level engineers. Strong React experience is the primary requirement; if you have that and are comfortable working across the stack, we would like to hear from you.
Note: In person final round interviews may be required for this role
Competitive total compensation package
401k plan
Medical, dental, and vision coverage
Flexible lifestyle wallet
Learning & development wallet
Flexible time off
Let’s build it together:
At Sift, we are intentionally building a diverse, equitable, and inclusive workplace. We believe that diversity drives innovation, equity is a fundamental right, and inclusion is a basic human need. We envision a place where all Sifties feel secure sharing their authentic selves and diverse experiences with their teams, their customers, and their community – ultimately using this empowerment and authenticity to build trust and create a safer Internet.
This document provides transparency around how Sift handles the personal data of job applicants: https://sift.com/recruitment-privacy
A little about us:
Sift is the AI-powered fraud platform securing digital trust for leading global businesses. Our deep investments in machine learning and user identity, a data network scoring 1 trillion events per year, and a commitment to long-term customer success empower more than 700 customers to grow fearlessly. Global brands rely on Sift to unlock growth and deliver seamless consumer experiences. Visit us at sift.com and follow us on LinkedIn.
At Sift, our Data Science team works at the core of our Digital Trust & Safety platform, helping customers stop fraud, abuse, and account takeover while protecting great user experiences. We partner closely with engineering, product, and go-to-market teams to turn large-scale behavioral data into practical machine learning improvements and customer value.
We are a forward-thinking team that challenges the status quo, values open and constructive feedback, and cares deeply about learning, rigor, and impact. We take pride in our work, not ourselves, and we believe machine learning is a powerful way to help internet businesses grow safely.
As a Data Scientist II at Sift, you will use data science and machine learning to improve fraud detection and customer outcomes. You will investigate fraud patterns, evaluate model behavior, prototype ideas, and work with engineering partners to translate research into production improvements. Your goal is to turn ambiguous customer and product problems into clear, data-driven recommendations that improve model quality, product capability, and business impact.
This is a strong fit for someone who enjoys both deep analysis and practical execution: someone who can dive into large datasets, frame the right questions, and communicate findings clearly to technical and non-technical partners alike.
Analyze fraud patterns, customer behavior, and model outcomes to identify opportunities for product and model improvements.
Partner with engineering and product teams to define evaluation metrics, investigate gaps in current product behavior, and propose practical improvements that drive customer value.
Design and run experiments on features, modeling approaches, and datasets to validate ideas and improve model performance.
Evaluate model quality through dataset analysis, error analysis, calibration, and score distribution investigations.
Build repeatable analyses, prototypes, and internal tools that support research, diagnosis, and operational decision-making.
Communicate findings and recommendations clearly across data science, engineering, and business stakeholders.
Bachelor’s degree in Computer Science, Statistics, Mathematics, a related technical field, or equivalent practical experience.
2+ years of relevant industry experience in data science, machine learning, analytics, or a closely related field.
Strong foundation in machine learning and data science best practices, with experience applying them to real-world problems.
Experience working with large datasets using tools such as Python, Jupyter, Pandas, PySpark, scikit-learn, PyTorch, TensorFlow, or similar technologies.
Comfort performing both deep analysis and lightweight prototyping to test ideas quickly.
Strong problem-solving skills and the ability to work effectively in ambiguous spaces with competing priorities.
Clear communication and collaboration skills, with a team-first mindset.
Experience in fraud, risk, trust and safety, cybersecurity, or adjacent domains.
Familiarity with Java or another object-oriented programming language.
Experience partnering closely with software engineers to productionize analytical or machine learning improvements.
Please note: Final round interviews may be held in person
Let’s build it together:
At Sift, we are intentionally building a diverse, equitable, and inclusive workplace. We believe that diversity drives innovation, equity is a fundamental right, and inclusion is a basic human need. We envision a place where all Sifties feel secure sharing their authentic selves and diverse experiences with their teams, their customers, and their community – ultimately using this empowerment and authenticity to build trust and create a safer Internet.
This document provides transparency around how Sift handles the personal data of job applicants: https://sift.com/recruitment-privacy
A little about us:
Sift is the AI-powered fraud platform securing digital trust for leading global businesses. Our deep investments in machine learning and user identity, a data network scoring 1 trillion events per year, and a commitment to long-term customer success empower more than 700 customers to grow fearlessly. Global brands rely on Sift to unlock growth and deliver seamless consumer experiences. Visit us at sift.com and follow us on LinkedIn.
As a Customer Solutions Engineer at Sift, you are the bridge between the customer-facing team and the engineering and product teams. You explain complex ideas to customers and relay customer needs to engineering and product. When a customer’s needs and our product don’t fully align, you’re the internal customer advocate who drives critical solution changes and refinements to our offerings.
What you’ll do:
Own the most complex customer issues: Customer Solutions Engineering is a team of highly technical customer-facing experts. You’ll partner closely with our Customer Success Management as the technical liaison to Enterprise/Strategic accounts, and make sure they maximize Sift value. This team is responsible for building a deep understanding of customers’ business problems, technical requirements and success criteria -- empowering customers to solve complex business problems.
Support the customer lifecycle: You will be the customer’s technical point of contact throughout their relationship with Sift, while also partnering with our Support team. You’ll understand the customer's business and technical needs. Day to day this involves understanding the nuances of their integration, working alongside Sift’s data science team to ensure the customer’s machine learning model health, meticulously whiteboarding the flow of their data to expand their integration, and being the internal voice of the customer. In short, you’ll do whatever it takes to make the customer successful.
Automate and Optimize: You will apply your deep technical and customer knowledge to help iterate on and improve internal and external processes. For some customers, you’ll write custom queries and scripts to calculate metrics to prove ROI, and optimize recurring processes. Internally, you will automate tasks, and take innovative approaches to problem-solving that will have the power to help guide internal decision-making.
What would make you a strong fit:
5+ years in a technical customer-facing role
Close cross-functional collaboration with data science, engineering and product
Outstanding communication skills, including the ability to communicate complex technical and business concepts to developers and non-developers
Creative, coachable, collaborative, goal-oriented, and thoughtful. You have a strong work ethic and are committed to excellence
You have a growth mindset - you enjoy learning new skills, and applying it to technical challenges
You are resourceful and proactive. If something seems strange, you’ll investigate. You are not afraid of challenging the status quo
Strong experience writing scripts and queries to build internal tools and data pulls (For example: SQL, Python, Bash scripting) and comfort with APIs and web technologies
Ability to prioritize, and deliver on multiple projects in tandem. You thrive under pressure and enjoy clarifying ambiguous situations
Bonus points for experience in the B2B payments and/or fraud space
Please note: Final round interviews may be held in person
Let’s build it together:
At Sift, we are intentionally building a diverse, equitable, and inclusive workplace. We believe that diversity drives innovation, equity is a fundamental right, and inclusion is a basic human need. We envision a place where all Sifties feel secure sharing their authentic selves and diverse experiences with their teams, their customers, and their community – ultimately using this empowerment and authenticity to build trust and create a safer Internet.
This document provides transparency around how Sift handles the personal data of job applicants: https://sift.com/recruitment-privacy
A little about us:
Sift is the AI-powered fraud platform securing digital trust for leading global businesses. Our deep investments in machine learning and user identity, a data network scoring 1 trillion events per year, and a commitment to long-term customer success empower more than 700 customers to grow fearlessly. Global brands rely on Sift to unlock growth and deliver seamless consumer experiences. Visit us at sift.com and follow us on LinkedIn.
Sift is hiring a Contracts and Legal Operations Specialist to run our contracting process end to end, including customer, vendor, and partner agreements. AI tools will handle first-pass review and drafting on routine paper; you take it from there, negotiating and closing standard agreements independently and escalating anything complex or high-risk to legal counsel. You'll also own the contract automation and playbooks going forward, tuning them as the business changes. The role works closely with Deal Desk, Sales, and Partners from a contracts perspective, along with finance, security, privacy, marketing, and product.
• Draft, negotiate, and close standard commercial agreements independently, including NDAs, order forms, standard renewals, and low-risk vendor and partner agreements, from first draft to signature.
• Review and finalize AI-generated first-pass redlines and clause extraction on incoming contracts before they go out to counterparties.
• Own the contract automation and playbooks over time: update clause libraries, adjust intake logic, and add new agreement types as the business changes.
• Manage vendor and procurement requests end to end: negotiate standard pricing and terms, track requests through Jira, and push back on terms that don't work for Sift.
• Manage the full contract lifecycle: intake, repository, renewals, approvals, and terminations.
• Coach Sales on standard terms and redlines so routine deals close without legal touching every file.
• Collaborate with Sales and Deal Desk to streamline the sales process and related deal cycles.
• Track and report on contract and vendor metrics.
• Triage inbound contracts and vendor requests, and escalate anything complex, high-risk, or outside standard terms to legal counsel.
• Take on other duties as part of a small, fast-moving legal and compliance team.
• 2+ years of experience in a contracts, legal operations, or deal desk role, ideally at a B2B SaaS company. No law degree required.
• Comfortable using AI tools daily to speed up drafting and review, not just occasionally.
• Good judgment on what's standard versus what needs to go to legal counsel.
• Experience with Salesforce and Jira.
• Strong organizational and time-management skills, with the flexibility to handle volume and competing requests.
• Comfortable working in a role that's still being built, where the process and tooling will keep changing.
• Prior legal, paralegal, or compliance experience.
• Experience with a CLM platform (e.g.,DocuSign Navigator, Ironclad, LinkSquares, Conga).
• Exposure to data privacy or DPA concepts (CPRA, GDPR).
• Experience in a fraud, risk, or trust & safety adjacent business.
• Hands-on experience using LLM tools (e.g., Claude, ChatGPT) to build things, not just chat: custom prompts, workflows, or lightweight automations.
• Prior experience working in a high-growth company.
Let’s build it together:
At Sift, we are intentionally building a diverse, equitable, and inclusive workplace. We believe that diversity drives innovation, equity is a fundamental right, and inclusion is a basic human need. We envision a place where all Sifties feel secure sharing their authentic selves and diverse experiences with their teams, their customers, and their community – ultimately using this empowerment and authenticity to build trust and create a safer Internet.
This document provides transparency around how Sift handles the personal data of job applicants: https://sift.com/recruitment-privacy
A little about us:
Sift is the AI-powered fraud platform securing digital trust for leading global businesses. Our deep investments in machine learning and user identity, a data network scoring 1 trillion events per year, and a commitment to long-term customer success empower more than 700 customers to grow fearlessly. Global brands rely on Sift to unlock growth and deliver seamless consumer experiences. Visit us at sift.com and follow us on LinkedIn.