Sr Data Scientist

Job Description

Technical & Solution Leadership Own and lead end-to-end AI/ML solution architecture for multiple Medicare Risk Adjustment initiatives spanning predictive modeling, NLP, GenAI, and operational analytics. Define analytics and AI strategy for assigned problem areas, ensuring scalability, robustness, regulatory compliance, and measurable business impact. Drive design decisions across data ingestion, feature engineering, model selection, evaluation, deployment, and monitoring. Establish and enforce engineering, modeling, and MLOps best practices across data science solutions. Advanced AI / ML & GenAI Innovation Lead development of advanced ML, deep learning, and LLM-based solutions (e.g., clinical reasoning, evidence extraction, summarization, coding intelligence). Evaluate and operationalize emerging AI approaches (agentic workflows, hybrid ML + rules, LLM orchestration, model ensembles). Ensure responsible AI usage-model explainability, bias monitoring, auditability, and CMS compliance. People & Capability Leadership Lead, mentor, and coach senior and junior data scientists, building strong technical depth and domain expertise within the team. Set technical direction, conduct design reviews, and guide complex problem solving. Support hiring, onboarding, and performance development for data science talent. Stakeholder Partnership & Executive Influence Act as a primary AI/ML advisor to senior business, clinical, and technology leaders. Translate complex analytics outcomes into clear, executive-level insights, risks, and recommendations. Partner with product, engineering, and operations teams to ensure successful adoption and downstream impact of AI solutions. Platform & Innovation Drive adoption of cloud-native, big-data, and MLOps frameworks across Python, Spark, Hive, Databricks, and cloud platforms. Own model lifecycle management, including versioning, performance tracking, drift detection, and continuous improvement. Ensure solutions meet enterprise standards for reliability, security, and scalability.

We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment regardless of their race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or recruiting process, please send a request to View email address on click.appcast.io learn more about how we collect, keep, and process your private information, please review Insight Global's Workforce Privacy Policy:

Skills and Requirements

-Education Bachelor's or Master's degree in Computer Science, Engineering, Statistics, Mathematics, Economics, or related quantitative field from a reputed institution.

-Experience Around 3 years+ of experience in Data Science, AI/ML, or Advanced Analytics. Demonstrated experience leading complex, production-grade AI/ML systems at scale.

-Prior experience mentoring or leading data scientists (formal or informal).

-Core Technical Expertise Expert proficiency in Python and PySpark.

-Deep hands-on experience with Spark, Hive, distributed data processing, and cloud platforms. --Strong command of ML algorithms, ensemble methods, and advanced feature engineering.

-Proven hands-on experience with deep learning frameworks (PyTorch and/or TensorFlow).

-Strong working knowledge of LLMs and Generative AI, including prompt design, orchestration, and evaluation.

-NLP & Healthcare Analytics Extensive experience with NLP/NLU (NER, summarization, classification, entity extraction), preferably on clinical or healthcare data.

-Strong understanding of statistical modeling, experimentation, and model validation.

-Leadership & Professional Skills Proven ability to drive ambiguity to clarity and own outcomes.

-Strong executive communication and storytelling skills.

-Ability to balance hands-on technical depth with strategic leadership.

-Demonstrated ownership mindset with high accountability and bias for action.

-Domain Expertise (Strongly Preferred)

-Deep understanding of Medicare Risk Adjustment and CMS programs.

-Hands-on experience with CMS datasets (MMR, MOR, EDPS, Encounter data).

-Experience working with clinical, coding, or claims data in healthcare environments.