Business Analytics Lead Analyst - HIH - Evernorth

The job profile for this position is HIH - Business Analytics Lead Analyst, which is a Band 3 Senior Contributor Career Track Role.

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About the Role

We are building a founding AI & Analytics team within Cigna Finance as part of the Finance Data Office in Hyderabad.
This is not a research lab, it’s a hands-on team that will define how Finance operates in the AI era. Our goal is simple: use AI and data to make Finance faster, smarter, and more efficient.

If you enjoy solving real business problems, building end-to-end AI solutions, and creating things that actually get used, this is the team to join.

What You’ll Work On

You’ll help us tackle some of Finance’s most important challenges — the ones that currently require manual effort, repeated checks, or slow hand-offs. Your work may include:

• Using LLMs, small LMs, GenAI, and NLP to understand complex contracts, guarantees, and rebate terms
• Building AI agents and automated workflows that simplify multi-step Finance processes
• Creating smarter forecasting and scenario-planning models that help teams make better decisions
• Automating business processes to speed up close activities and reduce manual work
• Designing solutions that reconcile data across systems and flag mismatches before they become issues
• Building reliable data pipelines that power AI models, reporting, and real-time insights

In short: you will make AI real inside Finance, embedded in daily operations, not sitting on the side as an experiment.

Who We’re Looking For

We’re not hiring for rigid job titles. We’re looking for builders, people who can understand a business problem, explore the data, and create a working solution.

You might be a great fit if you have:

Core Technical Skills

• Strong hands-on experience with Python, machine learning, and AI engineering
• Experience with GenAI, LLMs, small language models, RAG, and agentic AI
• Confidence designing and tuning NLP and predictive models
• Ability to build and manage data workflows on platforms like Databricks, or similar
• Strong prompt engineering fundamentals

Problem-Solving + Business Skills

• Ability to translate business needs into technical solutions
  • (e.g., “How can we improve cash forecasting accuracy, not just build another model?”)
• Comfort working with Finance datasets or ERP-related data
• Curiosity, adaptability, and the drive to build new solutions without a playbook
• Experience partnering with engineering teams and AI CoEs to productize models

Ways of Working

• Comfortable starting small, iterating quickly, and improving based on feedback
• Able to collaborate directly with global Finance stakeholders
• Experience working in global environments and empathy for end users

We value mindset as much as skillset, we want people who enjoy figuring things out and want to see their work make an impact.

Why This Role Is Exciting

This is a rare opportunity to build AI capabilities from the ground up inside a large, global organization.

You’ll get:

• The freedom to build and experiment
• The ability to see your work used by real Finance teams
• The chance to shape how Finance operates in the future
• Visibility and impact across multiple Finance functions

You won’t be executing someone else’s roadmap, you’ll help create it.

Qualifications & Experience

• 5-8  years in analytics, data science, or business intelligence with at least 5 years in a leadership or lead role.
• Experience delivering analytics or automation initiatives for Finance or FP&A functions.
• Knowledge of finance data domains such as general ledger, allocations, forecasting, and planning.
• Strong skills in tools like Power BI, Databricks, Microsoft Fabric, and Denodo.
• Familiarity with AI/ML frameworks (Python, TensorFlow, Azure ML) and emerging GenAI and automation tools.
• Certifications such as Azure AI Engineer or Data Science Professional are a plus.
• Strong communication and stakeholder management skills.

Please note that you must meet our posting guidelines to be eligible for consideration.  Policy can be reviewed at this link.