Gainwell - Senior Data Scientist

Summary :

As a Senior Data Scientist, you will support Gainwells Medicaid and public-sector analytics initiatives by leading advanced data science activities across complex healthcare and enterprise datasets. The role focuses on applying statistical modeling, machine learning, and scalable analytics techniques to generate actionable insights that inform business, clinical, and programmatic decisions.

Responsibilities :

- 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.

Required Skillset :

- Demonstrated expertise in developing and deploying machine learning models using Python, with a deep understanding of statistical modeling and its application to large-scale datasets.

- Proven ability to manage complex data workflows within Databricks and cloud computing environments, ensuring efficient processing and model performance.

- Strong proficiency in SQL for advanced data manipulation and the ability to derive actionable insights from complex relational databases.

- Advanced knowledge of NLP techniques and their application in processing healthcare-related text data to support clinical decision support systems.

- Exceptional communication skills with the ability to translate complex technical findings into clear, strategic recommendations for non-technical stakeholders.

- A collaborative mindset with the ability to thrive in a remote or distributed work environment, maintaining high levels of productivity and team engagement.

- A Master's degree or PhD in Computer Science, Statistics, Mathematics, or a related quantitative field, supported by 10 to 14 years of professional experience in data science and analytics.

(ref:hirist.tech)