Associate II, Analytics – Job Description
Ensemble
Overview
Ensemble is a leader in revenue cycle management innovation, leveraging advanced analytics and machine learning to deliver high-impact solutions.
The Associate II, Analytics role is focused on end-to-end machine learning (ML) development to optimize processes in healthcare revenue cycle management (RCM) operations. Candidates must have over 3 years of relevant experience to support data-driven decision-making in a dynamic environment. Please note, this is primarily an ML Engineer role, not a Data Scientist, or MLOps Role.
Job Responsibilities
- Contribute towards end-to-end ML development lifecycle, including data preparation, model building, deployment, and monitoring for revenue cycle applications.
- Build and optimize Gradient Boosting Trees models using LightGBM, and develop scikit-learn pipelines for predictive analytics.
- Implement Large Language Model (LLM) operations with OpenAI APIs, including summarization, prompt engineering, fine-tuning, and integration into operational workflows.
- Apply Explainable AI (XAI) techniques using libraries like SHAP and LIME to interpret model decisions and ensure transparency in high-stakes healthcare scenarios.
- Analyze complex datasets to identify patterns, develop deployable solutions, and collaborate on production-grade ML systems.
Required Skills
- Proficiency in Python and SQL for high-quality, production-ready code, with a public GitHub repository showcasing ML projects.
- MUST have actively programmed in python for 3 years
- SHOULD know SQL
- Expertise in ML libraries: scikit-learn, PySpark ML.
- Expertise in data manipulation libraries: pandas, Dask, Polars, PySpark.
- Expertise in data validation tools: Pydantic, Pandera.
- The right candidate should be able to pick up new technologies rapidly and contribute towards key initiatives.
- Hands-on experience with XAI libraries including but not limited to LIME, SHAP, BLEU, ROUGE etc.
- Strong knowledge of LLMs (OpenAI), including prompt engineering, tuning, and summarization tasks.
- Experience in healthcare or revenue cycle management is a plus.
Preferable Skills
- Exposure to healthcare analytics or revenue cycle management is advantageous but not mandatory. Such experience enhances the ability to apply ML solutions directly to domain-specific challenges in Ensemble’s operations. Candidates with this background can accelerate impact in revenue cycle optimization.
- Knowledge of Spark and experience in Databricks is a plus
Qualifications
- Undergraduate degree (B.E./B.Tech) in Engineering or Technology, or a graduate degree (M.Sc./M.S.) in Science, Mathematics, or Statistics (STEM).
- A first class, distinction, or top 10 percentile performance throughout the academic career is mandatory.
- Relevant experience exceeding 3 years is a key requirement alongside these academic credentials. People with a data/analytics background before the 3 years in ML Engineering with be preferred.