The Manager – Data Science is a hands‑on, player‑coach role within the Data Science Center of Enablement at Evernorth Health Services India. This role is designed for an experienced data science leader who combines strong technical depth with the ability to manage and develop small, high‑performing teams while partnering closely with business stakeholders.
The role requires a balance of:
Hands‑on data science execution
Technical leadership and mentorship
Business problem framing and solution design
This individual will work closely with US‑based business, data science, analytics, and engineering leaders to translate complex business problems into practical, scalable data science solutions, while maintaining a strong connection to the underlying models and analytical work.
Key Responsibilities
Hands‑On Data Science & Technical Leadership
- Remain actively hands‑on in applying statistics, classical machine learning, and advanced ML techniques to solve complex business problems.
- Design, develop, and evaluate predictive and analytical models, including regression, classification, tree‑based models, ensembles, and time‑series approaches.
- Guide feature engineering, model selection, validation, and performance optimization.
- Build and apply advanced machine learning and deep learning models where appropriate, using modern frameworks such as PyTorch and/or TensorFlow.
- Review and contribute directly to code, ensuring high standards of quality, performance, and maintainability.
Team Leadership & Development
- Manage and mentor a small team of data scientists, operating as a player‑coach.
- Provide technical guidance, constructive feedback, and hands‑on support to team members.
- Help develop team capability across statistics, machine learning, coding, and problem‑solving.
- Foster a culture of strong data science fundamentals, curiosity, and continuous learning.
Business Partnership & Problem Solving
- Partner closely with business and analytics stakeholders to understand business context, ask the right questions, and frame problems appropriately.
- Translate ambiguous business challenges into clear analytical problem statements and solution approaches.
- Collaborate with stakeholders to define success metrics, interpret results, and drive data‑backed decisions.
- Communicate insights, recommendations, and tradeoffs clearly to both technical and non‑technical audiences.
End‑to‑End Delivery & Collaboration
- Own data science initiatives end‑to‑end—from discovery and exploratory analysis through development, deployment support, and post‑launch evaluation.
- Partner with data engineering and platform teams to ensure solutions are scalable and production‑ready.
- Balance rigor with pragmatism, selecting the right level of model sophistication to meet business needs.
- Contribute to strengthening Evernorth India's data science practice, standards, and impact.
Education:
- Bachelor's or master's degree (PhD preferred) in Statistics, Mathematics, Computer Science, Data Science, Business or a related quantitative field from a top tier institute
Experience:
- 12+ years of experience in data science, analytics, or applied machine learning roles. Candidates from consulting background are preferred
- Prior experience leading or managing small teams of data scientists.
- Strong track record of delivering hands‑on analytical and ML solutions with measurable business impact.
- Experience working with large, complex datasets; healthcare, insurance, or pharmacy experience is a strong plus.
- Experience partnering with US‑based stakeholders in a global, matrixed environment is preferred.
Skills:
- Experience in consulting organizations for data science related engagements
- Strong foundation in probability, statistics, and classical machine learning algorithms.
- Advanced proficiency in Python and SQL.
- Hands‑on experience with ML libraries (e.g., scikit‑learn) and deep learning frameworks (PyTorch and/or TensorFlow).
- Solid understanding of the end‑to‑end data science and ML lifecycle.
- Ability to guide technical design decisions while remaining hands‑on.
- Strong business problem‑solving skills and analytical judgment.
- Clear, concise communicator capable of influencing stakeholders across business and technology.
- Comfort operating in ambiguity and owning outcomes across complex problem spaces.
