Data Scientist

Associate II, Analytics (Machine Learning Engineer)

Ensemble is a leading innovator in healthcare revenue cycle management (RCM), utilizing advanced analytics and machine learning to develop impactful solutions. This Associate II, Analytics position is centered on the complete machine learning (ML) development lifecycle, aiming to enhance processes within RCM operations. Ideal candidates will possess over 3 years of experience in data-driven decision-making within a fast-paced environment. Please note, this role primarily focuses on Machine Learning Engineering, rather than traditional Data Science or MLOps.

Responsibilities

• Contribute to the end-to-end ML development lifecycle, encompassing data preparation, model building, deployment, and monitoring for revenue cycle applications.
• Develop and optimize Gradient Boosting Trees models using LightGBM, and create scikit-learn pipelines for predictive analytics.
• Implement Large Language Model (LLM) operations via OpenAI APIs, including summarization, prompt engineering, fine-tuning, and integration into operational workflows.
• Apply Explainable AI (XAI) techniques with libraries such as SHAP and LIME to interpret model decisions and ensure transparency in critical healthcare contexts.
• Analyze complex datasets to identify patterns, create deployable solutions, and collaborate on production-grade ML systems.

Required Skills

• Proficiency in Python and SQL for developing high-quality, production-ready code, supported by a public GitHub repository demonstrating ML projects.
• Expertise in ML libraries: scikit-learn, LightGBM, PySpark ML.
• Expertise in data manipulation libraries: pandas, Dask, Polars, PySpark.
• Expertise in data validation tools: Pydantic, Pandera.
• Ability to rapidly acquire new technologies and contribute to key initiatives.
• Hands-on experience with XAI libraries including but not limited to LIME, SHAP, BLEU, ROUGE.
• Strong knowledge of LLMs (OpenAI), including prompt engineering, tuning, and summarization.
• 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. This experience can accelerate the application of ML solutions to domain-specific challenges within Ensemble's operations.
• Knowledge of Spark and experience in Databricks are 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).
• Mandatory requirement for first-class, distinction, or top 10 percentile academic performance.
• Relevant experience exceeding 3 years is a key requirement alongside academic credentials.
• Individuals with a data/analytics background prior to 3 years in ML Engineering will be preferred.