Lead Data Scientist – IntelliScript

Milliman

Lead Data Scientist responsible for developing innovative data-driven solutions for Milliman's insurance and healthcare clients. Collaborating with teams to enhance product offerings using AI and machine learning techniques.

Posted 7/16/2026full-timeBrookfield • Wisconsin • 🇺🇸 United StatesSenior💰 $117,500 - $249,780 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in developing and implementing AI/ML models for commercial data science solutions, with a strong focus on healthcare and life sciences. Proficient in leveraging generative AI and traditional machine learning techniques to drive innovation and improve internal capabilities.

Highest-signal resume keywords

AI/ML Model DevelopmentExpertise in Electronic Health RecordsDeep Learning ArchitecturesNLP AlgorithmsPython Programming

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Supervised LearningUnsupervised LearningModel ValidationGenAI ApplicationsData Science Solutions

Soft Skills

CollaborationCoachingContinuous Improvement

Tools & Technologies

DatabricksMlflowGitDockerAWS Lambda

Industry Keywords

HealthcareInsuranceLife SciencesData ScienceMachine Learning

Tech Stack

Tools & technologies

AWSCloudDockerLinuxPythonSQL

About the role

Key responsibilities & impact

Work in conjunction with our business development and product teams to develop and implement commercially viable model-based solutions to the healthcare, insurance, life sciences and adjacent markets
Research, develop, deploy, and maintain traditional AI/ML models following industry best practices
Work extensively with available GenAI models; construct exciting solutions to internal and external use cases across markets and enhance our internal capabilities through centralized internal tooling and thought leadership
Coordinate with Product, Business Development, ML Engineering, and IT to bring new and exciting data science products to market, as well as support existing industry leading products
Help drive best practices and continuous improvement on the data science team; influencing model design and experimentation strategy through planning, audit, peer review, and other coaching

Requirements

What you’ll need

10+ years of professional experience using AI/ML to create high return on investment commercial data science solutions
Expertise with Electronic Health Records or unstructured data analysis
Expert data scientist with demonstrable capability building traditional AI/ML models
Supervised Learning: Linear/logistic regression, decision trees, random forests, gradient boosting (XGBoost, LightGBM, CatBoost), and ensemble methods
Unsupervised Learning: K-means clustering, hierarchical clustering, PCA, and anomaly detection algorithms
Model Validation: Cross-validation strategies, hyperparameter optimization (Grid Search, Random Search, Bayesian optimization), and A/B testing frameworks
Deep Learning Architectures: Neural networks, transformers, and transfer learning methodologies
NLP Algorithms: Text preprocessing, TF-IDF, word embeddings (Word2Vec, GloVe), topic modeling (LDA), sentiment analysis, and named entity recognition
Expert understanding of NLP and generative AI; able to effectively use, fine-tune, and evaluate commercially available models as well as deploy and integrate local LLMs into the data science process
Hands-on experience building GenAI applications (e.g., RAG systems, LLM evaluation frameworks, or GenAI-powered internal tools)
Expert level Python programmer, with some experience in R and/or SQL
Expert user of Databricks or similar cloud-based model development ecosystem including mlflow, experimentation organization, data catalogs, and compute cluster configuration
Sufficient understanding of software engineering best practices such as Git for version control, unit testing, local development, and environment management
Knowledge of ML Engineering and ML Ops related concepts and tools including CICD pipelines, GitHub Actions, Docker, AWS Lambda, and Linux
Degree in a relevant field (computer science, data science, statistics, mathematics, applied math, actuarial science, economics, etc.)

Benefits

Comp & perks

Medical, Dental and Vision – Coverage for employees, dependents, and domestic partners
Employee Assistance Program (EAP) – Confidential support for personal and work-related challenges
401(k) Plan – Includes a company matching program and profit-sharing contributions
Discretionary Bonus Program – Recognizing employee contributions
Flexible Spending Accounts (FSA) – Pre-tax savings for dependent care, transportation, and eligible medical expenses
Paid Time Off (PTO) – Begins accruing on the first day of work. Full-time employees accrue 15 days per year, and employees working less than full-time accrue PTO on a prorated basis
Holidays – A minimum of 10 paid holidays per year
Family Building Benefits – Includes adoption and fertility assistance
Paid Parental Leave – Up to 11 weeks of paid leave for employees who meet eligibility criteria
Life Insurance & AD&D – 100% of premiums covered by Milliman
Short-Term and Long-Term Disability – Fully paid by Milliman