Data Science Advisor-HIH-Evernorth

The Advisor Data Science is a senior individualcontributor role within the Data Science Center of Excellence at Evernorth Health Services India. This role is designed for a highcaliber, handson 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 USbased analytics, data science, engineering, and business leaders to deliver highimpact analytical and ML solutions at scale. Key Responsibilities Operate as a senior individual contributor, owning complex data science initiatives endtoendfrom 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, treebased models, ensembles, timeseries) to solve realworld 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 productionquality 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 productionready. Translate ambiguous business problems into wellstructured analytical approaches and actionable insights. Communicate complex analytical results clearly to both technical and nontechnical 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 Indias data science maturity, credibility, and impact as a strategic analytics partner. Education: Bachelors or masters degree (PhD preferred) in Statistics, Mathematics, Computer Science, Data Science, or a related quantitative field from a top tier institute Experience: 8 years of experience in product management, AI/digital product development, analytics, or datadriven platform roles. Demonstrated experience working on AIenabled or advanced analytics products, with a strong understanding of where AI adds real business value and how it is operationalized. Strong handson experience with AI experimentation and iterative product development, including hypothesisdriven experimentation, rapid prototyping, A/B testing, pilots/POCs, and databacked decision making. Proven ability to design and run experiments to validate AI use cases, assess model and feature effectiveness, measure impact, and inform scaleup 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 tradeoffs, and buildvsbuy decisions. Strong background working across the full product lifecyclefrom problem discovery and value definition through technical design, delivery, adoption, and measurement. Experience partnering closely with USbased 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. Handson experience with ML libraries such as scikitlearn, and deep learning frameworks such as PyTorch and/or TensorFlow. Solid understanding of the endtoend 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 problemsolving skills. Ability to balance rigor with pragmatismchoosing the right level of model sophistication for the problem .