Lead Data Scientist - IntelliScript (Remote)
About The Position
Milliman IntelliScript is a business unit within Milliman, Inc., a respected consultancy. We develop and deploy data-driven, software-as-a-service (SaaS) products for clients in the insurance, health IT, and life sciences sectors. Our culture is entrepreneurial, collaborative, and focused on innovation, excellence, customer service, balance, and transparency. We offer sustained growth, opportunities for skill development, and a voice for every employee. Milliman invests in skills training, career development, and provides access to learning and mentoring opportunities. Employee Resource Groups (ERGs) influence policy, develop leaders, and amplify employee voices. We encourage employees to contribute to their professions and lead in professional organizations. Milliman is committed to its people, diversity and inclusion, social impact, and sustainability. The Lead Data Scientist will be integral to bringing innovative new products to market, leveraging expertise in data science, machine learning, GenAI, and NLP to enhance current product capabilities and develop new solutions. Projects will involve the construction, validation, documentation, and delivery of sophisticated GenAI and machine learning solutions for healthcare-related problems.
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; 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.).
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 across markets and enhance internal capabilities through centralized internal tooling and thought leadership.
- Coordinate with Product, Business Development, ML Engineering, and IT to bring new data science products to market and 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.
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
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What This Job Offers
Job Type
Full-time
Career Level
Senior
