Evernorth

specialty pharmacy operations

DataScienceLeadAnalyst

Hyderabad, India FULL TIME Remote Friendly
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Lead candidates.

The Brief

“Data Science Lead Analyst at Evernorth. Skills: AI/ML, GenAI, LLM, RAG pipelines, LangChain, Python, SQL. Lead the end-to-end development of AI/ML and GenAI solutions, from data exploration to deployment. Design and implement RAG pipelines, including document processing, embedding strategies, and retrieval optimization”

What You'll Achieve.

aligned with business outcomes

Industry & Context.

specialty pharmacy operations
Problems you'll solve

analytical thinking; problem-solving ability

Eligibility Requirements

Expected overlap with US hours as appropriate.

What They're Looking For.

Must Have

proficiency in Python and SQL with experience working on complex datasets, Solid understanding of machine learning techniques, model evaluation, and performance tuning, Bachelor’s or master’s degree in computer science, Engineering, Data Science, or related field, 5 - 8 years of experience in data science, AI/ML, or advanced analytics roles, Proven experience owning end-to-end solution delivery

Nice to Have

Experience in healthcare, pharmacy, or operational analytics domains, Exposure to cloud platforms (AWS preferred), Experience deploying LLM-based or hybrid AI systems into production

What You'll Do.

Lead the end-to-end development of AI/ML and GenAI solutions

from data exploration to deployment

Design and implement RAG pipelines

including document processing

and retrieval optimization

Build LLM-based applications using frameworks such as LangChain or similar orchestration tools

Develop workflows involving multi-step reasoning

or agent-like behaviors where appropriate

Translate business requirements into scalable analytical and technical solutions

Perform advanced data analysis and feature engineering using Python and SQL

Ensure solutions are measurable

and aligned with business outcomes

How You'll Work.

Team & Collaboration

Collaborate with engineering teams to productionize solutions via APIs and containerized services; Mentor junior team members and contribute to best practices in AI/ML development

Process & Methodology

owning end-to-end solution delivery

Full Job Description

**Data Science Lead Analyst** ** _Position Overview_** The Evernorth Innovation Hub (HIH) is seeking a Data Science Lead Analyst to drive the design and delivery of AI/ML and GenAI solutions supporting specialty pharmacy operations. This role serves as the primary technical owner of projects, responsible for translating business problems into working systems. This requires strong hands-on capability across both machine learning and modern AI approaches, including building LLM-powered applications and retrieval-based systems that operate reliably in production environments. **_Key Responsibilities_** * Lead the end-to-end development of AI/ML and GenAI solutions, from data exploration to deployment * Design and implement RAG pipelines, including document processing, embedding strategies, and retrieval optimization * Build LLM-based applications using frameworks such as LangChain or similar orchestration tools * Develop workflows involving multi-step reasoning, tool integration, or agent-like behaviors where appropriate * Translate business requirements into scalable analytical and technical solutions * Perform advanced data analysis and feature engineering using Python and SQL * Collaborate with engineering teams to productionize solutions via APIs and containerized services * Mentor junior team members and contribute to best practices in AI/ML development * Ensure solutions are measurable, explainable, and aligned with business outcomes ** _Qualifications_** **Required Skills** * Strong proficiency in Python and SQL with experience working on complex datasets * Solid understanding of machine learning techniques, model evaluation, and performance tuning * Hands-on experience with: * LLMs (prompt design, evaluation, handling limitations such as hallucination) * RAG systems (vector databases, embeddings, retrieval strategies) * Langchain or similar frameworks for orchestrating LLM workflows * Experience designing systems that combine structured data with unstructured t

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