Lead Data Scientist - IntelliScript (Remote)

Milliman•Brookfield, WI

1d•Remote

About The Position

Milliman IntelliScript is a business unit within Milliman, Inc., that develops and deploys data-driven software-as-a-service (SaaS) products for clients in the insurance, health IT, and life sciences industries. IntelliScript offers an innovative suite of products that interpret and deliver electronic medical data to aid clients in underwriting and pricing decisions. The company fosters an entrepreneurial, collaborative culture focused on innovation, excellence, customer service, balance, and transparency, with a commitment to employee growth and development. The Lead Data Scientist will be crucial in developing and launching new products, leveraging expertise in data science, machine learning, GenAI, and NLP to enhance existing capabilities and create new solutions. Projects will involve the construction, validation, documentation, and delivery of sophisticated GenAI and machine learning solutions for healthcare-related challenges.

Requirements

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.
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).
Proficiency in Model Validation: Cross-validation strategies, hyperparameter optimization (Grid Search, Random Search, Bayesian optimization), and A/B testing frameworks.
Knowledge of Deep Learning Architectures: Neural networks, transformers, and transfer learning methodologies.
Expertise in 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.
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.).
Excellent communication skills, in person and through phone / email.
Proven ability to understand client analytical needs, translate them into an action plan, then execute and deliver.
Customer-centric approach to finding solutions.
Focused on results and able to explain findings in a way that answers business problems.
Constructive, “can do” approach to overcoming obstacles.
Ability to quickly learn new techniques and technologies.
Proactive in identifying process improvements.
Strong work ethic, willing to pitch in wherever needed.
Thrive in a small team, without micromanagement.
Ability to manage projects and timelines, including directing the work of others.

Nice To Haves

PhD in relevant field or Actuarial designation (FCAS/FSA).
Experience in one of the following industries: healthcare, insurance (L&H or P&C), finance, life sciences, or similar fields.
Experience at an InsurTech or FinTech.
Past experience working in a HIPAA / PHI / PCI compliant environment.

Responsibilities

Work in conjunction with business development and product teams to develop and implement commercially viable model-based solutions for 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 solutions for internal and external use cases and enhance internal capabilities through centralized tooling and thought leadership.
Coordinate with Product, Business Development, ML Engineering, and IT to bring new data science products to market and support existing products.
Drive best practices and continuous improvement on the data science team, influencing model design and experimentation strategy through planning, audit, peer review, and coaching.

Benefits

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