Senior Data Scientist - IntelliScript (Remote)

Milliman•Brookfield, WI

2d•Remote

About The Position

Milliman IntelliScript is a business unit within Milliman, Inc., a respected consultancy with offices around the world. We develop and deploy category-defining, data-driven, software-as-a-service (SaaS) products for a broad spectrum of insurance, health IT and life sciences clients. We offer an entrepreneurial and collaborative culture of innovation, excellence, exceptional customer service, balance, and transparency. Every single person has a voice in our company, and we challenge each other to push the outer limits of our full, diverse potential. We reward excellence and offer competitive compensation and benefits. Milliman invests in skills training and career development and gives all employees access to a variety of learning and mentoring opportunities. Our growing number of Milliman Employee Resource Groups (ERGs) are employee-led communities that influence policy decisions, develop future leaders, and amplify the voices of their constituents. We encourage our employees to give back to their varied professions, including leadership in professional organizations. IntelliScript is a practice within Milliman that provides health and life insurers with real-time data and underwriting decision support tools via software-as-a-service (SaaS). IntelliScript offers an innovative suite of products which interpret and deliver electronic medical data (such as prescription histories, diagnoses, treatment data, etc.) to help our clients make effective underwriting and pricing decisions. Our company offers a unique entrepreneurial culture that also promotes work / life balance. IntelliScript has enjoyed consistent growth and is the leader in the markets we serve, where our scoring products are industry standards. The Senior Data Scientist will be integral as we continue to bring innovative new products to market in response to client needs and opportunities. The Senior Data Scientist will build upon their data science, machine learning, and/or GenAI and Natural Language Processing (NLP) expertise to develop intimate knowledge of our current product capabilities and provide advanced analytical expertise to enhance these products through new solutions. Projects will include construction, validation, documentation and delivery of sophisticated GenAI and machine learning solutions for a variety of healthcare-related problems.

Requirements

5+ years of professional experience using AI/ML to create high return on investment commercial data science solutions
Experience with Electronic Health Records or unstructured data analysis
Strong understanding traditional AI/ML model building approaches such as: 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
Strong 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)
Strong Python programmer, with some experience in R and/or SQL
Proficient 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
Awareness 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
Can 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

Master’s Degree 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 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 other data scientists as the team works 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; participating in 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