Professional Consultant - Remote

Position Overview

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.

Primary Responsibilities

• 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

Core Qualifications

• Education: Bachelor's or Master's degree in Computer Science, Engineering, Statistics, Mathematics, Economics, or related quantitative field from a reputed institution
• Experience: Around 6 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
• Able 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