Lead, Analytics (Data Science), Product Innovation

Job Title: Lead Analytics, Product Innovation

Experience: 6+ Years

Job Location: Hyderabad and Bangalore (Hybrid)

Company Overview:

Ensemble Health Partners India is at the forefront of innovation in the Revenue Cycle Management (RCM) space, leveraging modern technology to drive meaningful, real‑world impact. Our future‑ready platforms combine AI‑driven analytics, intelligent data ingestion, workflow automation, and business intelligence, built on a scalable, cloud‑native architecture.

Our AI‑powered solutions run in production environments, continuously optimizing processes and delivering actionable insights at scale. With the second‑largest market share in the U.S. RCM industry, a global workforce of 15,000+ professionals, and 12 technology patents, Ensemble delivers results through strong teams, mature processes, and modern technology platforms.

As part of our growth strategy, we have launched a Global Capability Center (GCC) in Hyderabad, serving as a strategic extension of our global operations. The GCC brings together technology, analytics, and RCM expertise to accelerate innovation and support our long‑term vision of transforming healthcare operations.

At Ensemble, we foster a culture of ownership, collaboration, and high performance, where your expertise is valued and your work creates measurable business impact.

Position Overview:

The Lead Analyst, Product Innovation drives the application of AI-enabled, data-driven capabilities across the Revenue Cycle Management (RCM) organization. This role is primarily focused on traditional machine learning model development—from problem framing and feature engineering through model training, evaluation, and deployment support—to improve decision-making and operational performance.

The Lead Analyst partners with product managers, engineers, data scientists, and operational stakeholders to assess business problems, explore feasibility, build prototypes, and evaluate impact. The role requires strong analytical capability, technical proficiency with Python, SQL, and the Azure ecosystem, and the ability to translate complex findings into actionable recommendations. Experience in LLM/GenAI is beneficial (e.g., prompt engineering, RAG, evaluation). Prior RCM industry experience is helpful. Candidates should demonstrate the ability to learn new domains quickly.

Core Competencies & Responsibilities

These representative competencies highlight what matters most for success in this role.

Machine Learning Model Development (Critical)

• Frames business problems into ML use cases; defines target variables, success metrics, and experimental approach.
• Builds, tunes, and evaluates traditional ML models (e.g., regression, classification, tree-based models, time series) and performs feature engineering, model validation, and performance monitoring.

Applied GenAI & LLM Enablement (Important)

• Applies LLM/GenAI capabilities where they add value (e.g., summarization, classification, extraction), including prompt design, RAG basics, and Python-based prototyping.
• Evaluates LLM output quality and risk (accuracy, bias, data leakage), and partners with engineering to translate prototypes into production-ready requirements.
  Technical Execution (Python + SQL + Azure)
• Builds prototypes leveraging Python, Azure OpenAI, SQL, and Azure ecosystem tools.
• Partners with engineering and data teams to validate data, refine requirements, and ensure scalable design.

Analytical Problem Solving

• Breaks down complex problems, analyzes root causes, and structures analytical approaches.
• Uses quantitative evidence to form recommendations.

Cross‑Functional Collaboration

• Works with operations, product, engineering, and AI teams.
• Contributes to requirements, design reviews, and prototype evaluations.

Clear Communication

• Synthesizes complex findings into clear insights, summaries, and stakeholder‑ready outputs.
• 
  

Essential Job Functions

• Translate business problems into ML use cases; define target outcomes, evaluation metrics, and baselines.
• Perform data exploration, feature engineering, and dataset creation using Python and SQL; validate data quality and lineage.
• Train, tune, and evaluate traditional ML models; run experiments, compare approaches, and document results and assumptions.
• Partner with engineering and data teams to support deployment patterns (batch/real-time), monitoring, and model performance tracking.
• Prepare stakeholder-ready insights, model performance summaries, and recommendations to inform product direction and prioritization.
• Ensure responsible use of data and models by following internal governance, privacy, and security standards; support documentation and auditability.
• Where relevant, prototype and evaluate GenAI/LLM components (e.g., prompt iterations, RAG inputs, output evaluation) to complement traditional ML solutions.
• Support cross‑functional sessions, requirements gathering, and documentation of solution designs.
  

Required Skills

• Experience:3–5 years in analytics or data science roles with hands-on experience building and evaluating traditional ML models in Python (e.g., scikit-learn) using structured data.
  • GenAI/LLMs: Familiarity with LLM applications and evaluation is a plus.
  • Domain: RCM/healthcare experience is helpful; ability to learn workflows and translate them into data/ML problems is expected.
• People Leadership: Not required.
• Education: Bachelor’s degree or equivalent experience.
• Preferred Study Areas: Computer Science, Analytics, or related fields.

Why Join US?

• Work on real‑world healthcare and technology challenges enabled by emerging technologies.
• Be part of a fast‑growing Global Capability Center with clear global ownership and impact.
• Thrive in a culture that values results, trust, accountability, and continuous improvement.
• Access structured learning, certifications, and long‑term career growth opportunities.
• Collaborate with high‑caliber technology and business leaders on meaningful initiatives.

Benefits

• Comprehensive health insurance coverage for associate, children (up to 2), and parents.
• Accidental insurance coverage.
• Professional development and certification reimbursement programs.
• Statutory benefits including maternity and paternity support.
• Thoughtful employee experiences such as welcome kits, company swag, and work‑anniversary recognition.
• Benefits designed to support you at different stages of life and career.