Job Title

The Senior Advisor – Data Science is a senior individual‑contributor role within the Data Science Center of Excellence at Evernorth Health Services India. This role is designed for a high‑caliber, hands‑on data scientist with strong foundations in statistics, classical machine learning, and modern AI techniques, combined with experience working across an advanced data science and ML stack.The role focuses on building, validating, and operationalizing data science solutions that solve complex business problems. It is not a governance or oversight role, but rather a role for an experienced practitioner who brings strong analytical judgment, technical depth, and the ability to influence solution design and execution across teams.This position partners closely with US‑based analytics, data science, engineering, and business leaders to deliver high‑impact analytical and ML solutions at scale.Key Responsibilities Operate as a senior individual contributor, owning complex data science initiatives end‑to‑end—from problem framing and exploratory analysis through model development, validation, and production support.Apply strong foundations in statistics and classical machine learning (e.g., regression, classification, tree‑based models, ensembles, time‑series) to solve real‑world business problems.Design, develop, and evaluate predictive and analytical models using rigorous statistical and ML techniques.Perform feature engineering, model selection, tuning, and performance evaluation, clearly articulating assumptions and tradeoffs.Build and apply advanced machine learning and deep learning models where appropriate, using modern frameworks such as PyTorch and/or TensorFlow.Write clean, efficient, and production‑quality code, following strong software engineering and data science best practices.Partner closely with data engineering and platform teams to ensure models are scalable, reliable, and production‑ready.Translate ambiguous business problems into well‑structured analytical approaches and actionable insights.Communicate complex analytical results clearly to both technical and non‑technical stakeholders, focusing on business impact.Provide technical guidance and informal mentorship to junior data scientists, helping raise the overall quality of data science practice.Contribute to strengthening Evernorth India’s data science maturity, credibility, and impact as a strategic analytics partner.Education:Bachelor’s or master’s degree (PhD preferred) in Statistics, Mathematics, Computer Science, Data Science, or a related quantitative field from a top tier instituteExperience:15+ years of experience in AI/digital product development, analytics, or data‑driven platform roles.Demonstrated experience working on AI‑enabled or advanced analytics products, with a strong understanding of where AI adds real business value and how it is operationalized.Strong hands‑on experience with AI experimentation and iterative product development, including hypothesis‑driven experimentation, rapid prototyping, A/B testing, pilots/POCs, and data‑backed decision making.Proven ability to design and run experiments to validate AI use cases, assess model and feature effectiveness, measure impact, and inform scale‑up or pivot decisions.Proven ability to operate as a senior advisor or product thought leader, influencing without formal authority across product, engineering, and architecture stakeholders.Experience collaborating deeply with engineering and platform teams, participating in architecture discussions, design trade‑offs, and build‑vs‑buy decisions.Strong background working across the full product lifecycle—from problem discovery and value definition through technical design, delivery, adoption, and measurement.Experience partnering closely with US‑based product and technology leaders in a global, matrixed environment.Experience in healthcare, insurance, pharmacy, or other regulated industries is strongly preferred.Skills: Strong foundation in probability, statistics, and classical machine learning algorithms.Advanced proficiency in Python and SQL.Hands‑on experience with ML libraries such as scikit‑learn, and deep learning frameworks such as PyTorch and/or TensorFlow.Solid understanding of the end‑to‑end data science and ML lifecycle, including development, validation, deployment, and monitoring.Familiarity with cloud or distributed computing environments and production ML concepts.Strong analytical thinking and problem‑solving skills.Ability to balance rigor with pragmatism—choosing the right level of model sophistication for the problem.Clear, concise communication skills with the ability to influence without formal authority.Comfort operating in ambiguity and owning outcomes across complex problem spaces.