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Senior Data Scientist
Skills
Artificial IntelligenceBusinessBusiness InsightsData ScienceMachine LearningMeasurementsPattern Recognition
What the job involves
The main requirements, responsibilities and hiring steps.
Requirements
- 6+ years of data science experience with applied machine learning in production
- Strong experience with recommendation systems ranking models or personalization
- Solid grounding in statistics experimentation A/B testing and incrementality measurement
- Experience with causal inference methods for observational data
- Proficiency in Python and SQL with large-scale datasets
- Experience with event-driven or transaction-level data
- Familiarity with modern data and ML stacks including Spark Airflow dbt feature stores and cloud platforms
- Experience collaborating with engineers to deploy models into production systems
- Ability to connect modeling work to business outcomes like conversion lift retention and ROI
- Strong communication skills for technical and non-technical audiences
- U.S. core business hours availability and willingness to travel for company meetings
Nice to have
- Pragmatic
- Product-minded
- Impact-driven
Day to day
- Build and ship machine learning models for offer personalization ranking and targeting using transaction merchant and behavioral data
- Develop features and training pipelines from large-scale event and transaction datasets to improve model performance
- Design analyze and interpret A/B tests incrementality experiments and causal measurement methods to quantify ROI and user behavior changes
- Partner with engineering and product teams to productionize models monitor performance and translate insights into actionable recommendations
