Design, develop, and execute analytical solutions using optimization, simulation, machine learning, generative AI, and statistical modeling.
Construct predictive models to explain events, forecast behaviors, identify risk, or perform segmentation and clustering.
Apply domain expertise to ensure models are practical, interpretable, and aligned with business needs.
Evaluate alternative approaches and select appropriate modeling techniques for each use case.
Integrate and transform large volumes of data from diverse sources to support analytics and experimentation.
Build modeling-ready datasets using validation, reconciliation, feature engineering, and aggregation techniques.
Write complex SQL queries involving multi-table joins, data exploration, and troubleshooting with minimal guidance.
Develop logical data models combining internal and external datasets; lead conversations with external data providers when needed.
Build automated analytics pipelines leveraging scripting, APIs, DevOps practices, and cloud platforms.
Partner with engineering and IT teams to scale solutions, automate workflows, and integrate models into business processes.
Develop and deliver clear, compelling visualizations tailored to various audiences.
Interpret analytical results and communicate actionable insights that influence senior leaders and key business partners.

Bachelor's in a quantitative field required (Master’s/PhD preferred)
6+ years of experience in data science or machine learning
Strong Python and SQL skills
Experience with cloud platforms (AWS preferred; Azure/GCP comparable)
Databricks + PySpark experience is a strong plus
Background in statistical modeling, ML algorithms, and feature engineering
Ability to build automated analytics workflows and work with APIs
Strong communication skills with experience influencing senior stakeholders
Entrepreneurial mindset, curiosity, and comfort working in fast-moving environments

Senior Data Scientist – GenAI, Python, AWS, SQL

Key skills