Having 10 or more years of experience, this position will be responsible for leading and supporting data science initiatives across the full analytics lifecycle.
Lead data ingestion, cleansing, transformation, and aggregation efforts for large scale and complex datasets.
Design and implement advanced feature engineering, statistical estimation, and hypothesis testing techniques.
Develop, validate, and refine machine learning and statistical models, including time series, repeated measures, and mixed effects models.
Ensure analytical rigor by addressing overfitting, false discovery, bias, and model generalizability.
Analyze healthcare and enterprise datasets to surface complex, high impact, actionable insights that support strategic decision making.
Drive iterative model development and support continuous integration and deployment of analytics solutions.
Optimize data science solutions for performance, scalability, and production readiness.
Leverage cloud based platforms to support elastic, high volume data science workloads.
Collaborate with business stakeholders, data engineers, architects, and analysts to align analytics outputs with business objectives.
Provide technical leadership and guidance to junior data scientists and analysts.
Contribute to the definition and evolution of data science standards, best practices, and reusable analytics assets.
Clearly document analytical methodologies, assumptions, results, and recommendations.
Present insights and recommendations effectively to technical and non technical stakeholders, including leadership audiences.
