As a Senior Software Engineer your role will be to:
Play a key role in the design and architecture of cutting-edge, innovative data systems.
Develop and maintain a multi-tenant environment for our advanced measurement solutions.
Build and manage cloud-based, distributed computing environments to support scalable, high-performance operations.
Design and implement robust ETL workflows, integrating multiple data sources for cleaning, transformation, aggregation, and querying.
Troubleshoot and resolve complex issues related to data integration, storage, and retrieval.
Architect and build big data solutions capable of managing and automating the processing of tens of terabytes.
Optimize database performance and streamline query execution in large-scale environments.
Collaborate closely with Data Scientists to align technical solutions with data-driven objectives.
You will also participate in important decisions around the product, our strategy as well as have the opportunity to choose the areas you work on based on what you want or like to do the most. We believe in helping each other get most of ourselves rather than do what we’re not interested in doing.
Key Requirements:
At least 10 years of professional experience in backend software development (Python preferred) with a strong focus on data-related projects.
Proven experience working in microservices environments and cloud platforms.
Expertise in distributed applications and systems.
Create large-scale data processing pipelines to help developers build and train novel machine learning algorithms. (Pandas, NumPy, Dask, Argo).
Deep understanding of relational databases, data warehouses, advanced knowledge of SQL for crafting efficient queries
Hands-on experience in bringing applications to production and maintaining production environments.
Strong problem-solving skills, with a passion for troubleshooting and optimizing complex systems.
Familiarity with containerization technologies like Docker and Kubernetes.
Strong communication and collaboration skills, with a track record of working effectively in cross-functional teams.
Comfort with experimenting and adopting new technologies to stay ahead of the curve.
Familiarity with DevOps practices and tools to support the full development lifecycle.
Ability to multitask, prioritize, and manage time effectively in a fast-paced environment.
Some of the technologies we use: Python, Argo, Kubernetes, Spark, etc…
","descriptionPlain":"As a Senior Software Engineer your role will be to:\n\n - Play a key role in the design and architecture of cutting-edge, innovative data systems.\n\n - Develop and maintain a multi-tenant environment for our advanced measurement solutions.\n\n - Build and manage cloud-based, distributed computing environments to support scalable, high-performance operations.\n\n - Design and implement robust ETL workflows, integrating multiple data sources for cleaning, transformation, aggregation, and querying.\n\n - Troubleshoot and resolve complex issues related to data integration, storage, and retrieval.\n\n - Architect and build big data solutions capable of managing and automating the processing of tens of terabytes.\n\n - Optimize database performance and streamline query execution in large-scale environments.\n\n - Collaborate closely with Data Scientists to align technical solutions with data-driven objectives.\n\nYou will also participate in important decisions around the product, our strategy as well as have the opportunity to choose the areas you work on based on what you want or like to do the most. We believe in helping each other get most of ourselves rather than do what we’re not interested in doing.\n\nKey Requirements:\n\n - At least 10 years of professional experience in backend software development (Python preferred) with a strong focus on data-related projects.\n\n - Proven experience working in microservices environments and cloud platforms.\n\n - Expertise in distributed applications and systems.\n\n - Create large-scale data processing pipelines to help developers build and train novel machine learning algorithms. (Pandas, NumPy, Dask, Argo).\n\n - Deep understanding of relational databases, data warehouses, advanced knowledge of SQL for crafting efficient queries\n\n - Hands-on experience in bringing applications to production and maintaining production environments.\n\n - Strong problem-solving skills, with a passion for troubleshooting and optimizing complex systems.\n\n - Familiarity with containerization technologies like Docker and Kubernetes.\n\n - Strong communication and collaboration skills, with a track record of working effectively in cross-functional teams.\n\n - Comfort with experimenting and adopting new technologies to stay ahead of the curve.\n\n - Familiarity with DevOps practices and tools to support the full development lifecycle.\n\n - Ability to multitask, prioritize, and manage time effectively in a fast-paced environment.\n\nSome of the technologies we use: Python, Argo, Kubernetes, Spark, etc…","compensation":{"compensationTierSummary":null,"scrapeableCompensationSalarySummary":null,"compensationTiers":[],"summaryComponents":[]}},{"id":"5ad9c6e6-a89f-4d46-af8c-da2b6977c2bb","title":"Senior Product Manager","department":"Product","team":"Product","employmentType":"FullTime","location":"IL | Ramat Gan","shouldDisplayCompensationOnJobPostings":false,"secondaryLocations":[],"publishedAt":"2026-07-14T12:51:36.507+00:00","isListed":true,"isRemote":true,"workplaceType":"Hybrid","address":{"postalAddress":{"postalCode":"5252181","addressRegion":"Tel Aviv District","streetAddress":"HaHarkon St. 4 ","addressCountry":"Israel","addressLocality":"Ramat Gan"}},"jobUrl":"https://jobs.ashbyhq.com/incrmntal/5ad9c6e6-a89f-4d46-af8c-da2b6977c2bb","applyUrl":"https://jobs.ashbyhq.com/incrmntal/5ad9c6e6-a89f-4d46-af8c-da2b6977c2bb/application","descriptionHtml":"As a Senior Product Manager at INCRMNTAL, you will sit at the intersection of data science, engineering, and product, translating complex ML and causal inference capabilities into a product our customers love. You will work hand-in-hand with our data science and the engineering teams to shape how models are designed, evaluated, and delivered into production.
Own a significant part of the product roadmap for our value measurement platform, with a focus on data science driven features (causal inference, incrementality modeling, attribution, and media mix optimization) and customer onboarding.
Partner closely with data scientists from problem framing through experimentation, model validation, and productization, you’ll be expected to critically read model specs, challenge assumptions, and help prioritize research directions based on customer impact
Define success metrics and evaluation frameworks for ML models alongside the DS team, balancing statistical rigor with business usability
Own the UX of data-heavy features: collaborate with designers and data scientists to turn complex model outputs into intuitive user flows, clear visualizations, and dashboards that customers can actually act on
Design and prioritize dashboards, reports, and in-product analytics, defining what metrics to surface, how to visualize uncertainty and causal results, and how to make insights discoverable without overwhelming the user
Run user research and customer interviews to validate both the analytical value and the usability of features, and onboarding integration; translate findings into concrete design and product improvements
Translate customer problems into well-scoped technical and design requirements; translate model outputs and methodology into clear value propositions for customers
Prepare the implementation of features and support engineering, design, and DS teams through design reviews, QA, and launch, including writing acceptance criteria that account for model behavior, edge cases, data quality, and UX states (empty, loading, partial data, error)
Ensure data integrity through testing, acceptance tests, and ongoing monitoring across our diverse range of data products
Work with clients and internal stakeholders to understand business goals, identify relevant KPIs, and feed those insights back into the product, modeling, and dashboarding roadmap
Oversee end-to-end data flow and engineering processes, collaborating with ML, data, and engineering teams to ensure efficient and accurate operation during critical phases like client onboarding and daily production runs
Strategically plan for missing or imperfect data, designing product behavior and UX for new client onboarding, process failures, client-specific configurations, long-term seasonality, and external signals/features
Drive experimentation: help design A/B tests, back-tests, and validation studies to assess the impact of new models, features, and UX changes
Key Requirements:
Min. 4 years of work experience in a product management role, experience in SaaS, B2B and/or data-heavy / ML-driven products is strongly preferred
Proven track record of shipping products that involve machine learning, statistical modeling, or data pipelines, comfortable being the PM counterpart to a data science team
Technical fluency: able to read and discuss ML/statistical concepts (regression, causal inference, Bayesian methods, time series) with data scientists, and able to reason about trade-offs in model design
Hands-on comfort with SQL and the ability to independently query, explore, and validate data; familiarity with Python (notebooks, basic scripting) is a strong plus
Understanding of data infrastructure concepts, ETL/ELT pipelines, data quality, distributed processing (Spark, Kubernetes, Argo, or similar), enough to collaborate meaningfully with engineering
Strong UX sensibility for data products, experience partnering with designers to turn complex data and model outputs into clear, usable interfaces; comfort working in Figma (reviewing, commenting, and prototyping); a strong eye for data visualization and how to communicate uncertainty, causal results, and KPIs to non-technical users
Experience shaping dashboards and in-product analytics, defining what to surface, how to structure it, and how users will interpret and act on it
Hands-on experience with product integrations and data connectors, understanding how customers bring their data in (APIs, SDKs, MMPs, ad platforms, server-to-server integrations, data warehouses), and how to design onboarding flows that handle authentication, data mapping, validation, and error states
Familiarity with third-party integrations in the ad-tech ecosystem (e.g., Google Ads, Meta, TikTok, AppsFlyer, Adjust, Snowflake, BigQuery) is a big plus
Knowledge of agile development practices (Scrum, Kanban)
Strong analytical skills, conceptual thinking, and a structured work approach
Excellent written and verbal communication, able to translate between DS, engineering, design, and commercial stakeholders
Familiarity with advertising, digital marketing, analytics, attribution, or tracking is a big plus
BSc or higher in a quantitative field (Computer Science, Statistics, Mathematics, Engineering, Physics, or similar) is a plus
Role Description:
As a Staff Data Scientist your role will be to:
Use analytical, statistical and technical skills to understand large, complex datasets with the aim to eliminate waste and measure incrementality for advertisers.
Lead, Develop & improve algorithms for automated decision making around lifetime value, causality, multi-touch attribution, and media mix optimization
Determine, analyze, maintain, and report on core marketing metrics to identify causal relationships between marketing actions and outcomes.
Translate data into actions and recommendations – appropriately interpreting and building on findings, and fully exploiting insights
You will also participate in important decisions around the product, our strategy as well as have the opportunity to choose the areas you work on based on what you want or like to do the most. We believe in helping each other get most of ourselves rather than do what we’re not interested in doing.
Key Requirements:
Min. 8 years of work experience in a commercial data science environment that requires the combined application of statistical & engineering skills
Strong statistical and research skills with a track record of using a variety of math and statistical methods (especially Causal Inference, Prediction models, Bayesian Method)
Excellent development skills (Python required, R or Scala a plus)
Experience in working on big data with distributed computing (Spark, Airflow, Kubernetes)
Familiarity with digital marketing, advertising or analytics is a plus
Extensive experience in the Time Series domain, working with small and large time series frames
Theoretical background knowledge like from a relevant BSc, MSc or PHD is a big advantage (e.g. in Mathematics, Computer Science, Statistics, Physics)
Role Description:
As a Senior Business Analyst your role will be:
Collaborate with clients to uncover insights about their marketing incrementality performance and paid-channel efficiency.
Deliver benchmarking analyses to provide clients with context on how they perform relative to industry standards and peers.
Design and execute analyses to answer challenging business questions, including those that are ambiguous or unstructured.
Proactively identify opportunities to help clients optimize their performance using INCRMNTAL's measurement solutions.
Leverage statistical methods and advanced analytics to uncover trends and provide actionable recommendations.
Work directly with large datasets using SQL to extract, analyze, and interpret data.
Collaborate with Product and Engineering teams to enhance the analytics capabilities of the platform, ensuring customer needs are met.
Create and maintain visually compelling reports and dashboards to communicate findings effectively.
Partner closely with Product, Customer Success, and Sales teams to understand customer challenges and drive the adoption of data-driven solutions.
Provide feedback to the Product team to improve features and usability based on customer insights and hands-on experience.
Act as a subject matter expert on marketing measurement and incrementality, sharing insights with customers and internal teams.
Stay ahead of industry trends, emerging measurement methodologies, and market developments.
Key Requirements:
4+ years in marketing science and/or marketing analytics roles, preferably within the adtech / marketing tech ecosystem or a measurement-focused company.
Strong proficiency in SQL and experience with cloud-based analytics platforms (e.g., Amazon Athena, Google BigQuery).
Familiarity with statistical tools (e.g., R, Python) and data visualization platforms (e.g., Tableau, Looker).
Self-motivated and independent, with a proven ability to manage multiple projects and deliver high-quality results.
Exceptional communication and storytelling skills, capable of presenting complex data insights to both technical and non-technical audiences.
Bonus Point:
Understanding of incrementality measurement and marketing efficiency methodologies.
","descriptionPlain":"Role Description:\n\nAs a Senior Business Analyst your role will be:\n\n - Collaborate with clients to uncover insights about their marketing incrementality performance and paid-channel efficiency.\n\n - Deliver benchmarking analyses to provide clients with context on how they perform relative to industry standards and peers.\n\n - Design and execute analyses to answer challenging business questions, including those that are ambiguous or unstructured.\n\n - Proactively identify opportunities to help clients optimize their performance using INCRMNTAL's measurement solutions.\n\n - Leverage statistical methods and advanced analytics to uncover trends and provide actionable recommendations.\n\n - Work directly with large datasets using SQL to extract, analyze, and interpret data.\n\n - Collaborate with Product and Engineering teams to enhance the analytics capabilities of the platform, ensuring customer needs are met.\n\n - Create and maintain visually compelling reports and dashboards to communicate findings effectively.\n\n - Partner closely with Product, Customer Success, and Sales teams to understand customer challenges and drive the adoption of data-driven solutions.\n\n - Provide feedback to the Product team to improve features and usability based on customer insights and hands-on experience.\n\n - Act as a subject matter expert on marketing measurement and incrementality, sharing insights with customers and internal teams.\n\n - Stay ahead of industry trends, emerging measurement methodologies, and market developments.\n\nKey Requirements:\n\n - 4+ years in marketing science and/or marketing analytics roles, preferably within the adtech / marketing tech ecosystem or a measurement-focused company.\n\n - Strong proficiency in SQL and experience with cloud-based analytics platforms (e.g., Amazon Athena, Google BigQuery).\n\n - Familiarity with statistical tools (e.g., R, Python) and data visualization platforms (e.g., Tableau, Looker).\n\n - Self-motivated and independent, with a proven ability to manage multiple projects and deliver high-quality results.\n\n - Exceptional communication and storytelling skills, capable of presenting complex data insights to both technical and non-technical audiences.\n\nBonus Point:\n\nUnderstanding of incrementality measurement and marketing efficiency methodologies.","compensation":{"compensationTierSummary":null,"scrapeableCompensationSalarySummary":null,"compensationTiers":[],"summaryComponents":[]}}],"apiVersion":"1"}