Oliver Wyman - Sr. Lead Data Scientist or Principal Data Scientist

Boston, Chicago, New York, Dallas, Toronto, Montreal

Lead Data Scientist Role and Responsibilities As a Lead Data Scientist, you will primarily manage technical projects—including data engineering, model selection and design, and infrastructure deployment in internal and client environments. You will work across diverse industries and teams, partnering with Oliver Wyman partners and engaging with clients to craft and deliver data‑driven solutions.

Exploring data, building models, and evaluating solution performance to resolve core business problems

Explaining, refining, and collaborating with stakeholders through the journey of model building

Keeping up with your domain’s state of the art & developing familiarity with emerging modelling and data engineering methodologies

Advocating application of best practices in modelling, code hygiene and data engineering

Leading the development of proprietary statistical techniques, algorithms or analytical tools on projects and asset development

Working with Partners and Principals to shape proposals that leverage our data science and engineering capabilities

Experience & Qualifications

Technical background in computer science, data science, machine learning, artificial intelligence, statistics, or other quantitative and computational science

Compelling track record of designing and deploying large-scale technical solutions, which deliver tangible, ongoing value including:

Building and deploying robust, complex production systems that implement modern data science methods at scale, including supervised learning (regression and classification with linear and non‑linear methods) and unsupervised learning (clustering, matrix factorization methods, outlier detection, etc.)

Leveraging cloud‑based infrastructure‑as‑code (CloudFormation, Bicep, Terraform, etc.) to minimize deployment toil and enable solutions to be deployed across environments quickly and repeatably

Demonstrating comfort and poise in environments where large projects are time‑boxed, and therefore consequential design decisions may need to be made and acted upon rapidly

Demonstrated fluency in modern programming languages for data science (i.e. at least Python, other expertise welcome), covering the full ML lifecycle (e.g. data storage, feature engineering, model persistence, model inference, and observability) using open‑source libraries, including:

Knowledge of one or more machine learning frameworks, including but not limited to: Scikit‑Learn, TensorFlow, PyTorch, MxNet, ONNX, etc.

Familiarity with the architecture, performance characteristics and limitations of modern storage and computational frameworks, with cloud‑first considerations for Azure and AWS particularly welcome

A history of compelling side projects or contributions to the Open‑Source community is valued but not required

Solid theoretical grounding in the mathematical core of the major ideas in data science:

Deep understanding of a class of modelling or analytical techniques (e.g. Bayesian modelling, time‑series forecasting, etc.)

Fluency in the mathematical principles and generalizations of data science – e.g., Statistics, Linear Algebra and Vector Calculus

Experience presenting at high‑impact data science conferences and solid connections to the data science community (e.g., via meetups, continuing relationships with academics, etc.) is highly valued

Interest/background in Financial Services, and capital markets in particular, Healthcare and Life Sciences, Consumer, Retail, Energy, or Transportation industries

Your Attributes

An undergraduate or advanced degree from a top academic program

A genuine passion for technology and solving problems

A pragmatic approach to solutioning and delivery

Excellent communication skills, both verbal and written

A clear commitment to creating impactful solutions that solve our clients’ problems

The ability to work fluidly and respectfully with our incredibly talented team

Willingness to travel for targeted client and/or internal stakeholder meetings

Compensation and Benefits The applicable base salary range for this role is $150,000 to $195,000. The base pay offered will be determined based on experience, skills, training, location, certifications, and education, and any applicable minimum wage requirements. The position may also be eligible for performance‑based incentives. It includes health and welfare benefits, tuition assistance, 401K savings, and other retirement programs, and employee assistance programs.

Oliver Wyman is an equal opportunity employer. Marsh McLennan and its Affiliates are EOE Minority/Female/Disability/Vet/Sexual Orientation/Gender Identity employers.

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