Were looking for an Applied Data Scientist to help us build and scale the core marketing science products that power our platform. This role sits at the intersection of data science and engineering: owning statistical models end to end, deploying them into production, and turning advanced analytics into reliable, customer‑facing capabilities. Your work will directly influence how thousands of brands measure ROI and allocate millions in marketing spend.
What Youll Do:
Build marketing measurement and optimization products (e.g., attribution models, MMM, incrementality testing, forecasting systems)
Develop and deploy statistical and machine learning models to production
Create scalable data pipelines and APIs that serve real-time analytics
Partner closely with Product, Engineering, and other stakeholders to translate business questions into clear analytical solutions.
Own features end to end from statistical design and validation through deployment, monitoring, and iteration.
Requirements: What Youll Bring:
4-7 years of experience in applied data science
Ability to work from our Jerusalem office (located in the Central Bus Station next to the train) 2 times a week (Monday & Wednesday) is required
Strong Python skills (pandas, scikit-learn, statistical libraries)
Experience deploying models to production (not just notebooks)
Solid statistics and machine learning fundamentals
SQL and database experience
Experience in building APIs or backend services
Bachelor's or Master's in a quantitative field (Statistics, CS, Math, Machine Learning/Data Science)
Strong English communication skills with technical and non-technical audiences
Self-starter comfortable with ambiguity and autonomy
Bonus Points If You Bring:
Marketing analytics background (attribution, experimentation, measurement)
Bayesian statistics or causal inference experience
Cloud platform knowledge (GCP, AWS, or Azure)
Time series analysis and forecasting.
This position is open to all candidates.