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

Lead Data Scientist – Locations: Boston, Chicago, New York, Dallas, Toronto, Montreal

The Role And Responsibilities

• Exploring data, building models, and evaluating solution performance to resolve core business problems
• Explaining, refining, and collaborating with stakeholders through the model‑building journey
• Keeping up with the domain’s state‑of‑the‑art and familiarizing with emerging modelling and data engineering methodologies
• Advocating 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

Your 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 that deliver tangible, ongoing value, including:
  • Building and deploying robust, complex production systems that implement modern data‑science methods at scale (supervised and unsupervised learning)
  • Leveraging cloud‑based infrastructure‑as‑code (CloudFormation, Bicep, Terraform, etc.) to minimize deployment toil and enable rapid deployments
  • Demonstrating comfort and poise in time‑boxed environments where rapid design decisions are required
• Fluency in modern programming languages for data science (e.g., Python) covering the full ML lifecycle using open‑source libraries:
  • Knowledge of one or more machine‑learning frameworks such as 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
  • History of side projects or contributions to the open‑source community (valued but not required)
• Solid theoretical grounding in the mathematical core of data science:
  • Deep understanding of a class of modelling or analytical techniques (e.g., Bayesian modeling, time‑series forecasting, etc.)
  • Fluency in the mathematical principles and generalizations of data science – statistics, linear algebra, and vector calculus
• Experience presenting at high‑impact data‑science conferences and solid connections to the data‑science community (e.g., meetups, academic relationships) highly valued
• Interest/background in financial services, capital markets, 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

Our Values & Culture

• Rewarding work – our reputation for high‑quality work and strong client relationships creates challenging, supportive, and recognized projects
• Progressive employment – flat structures, I&D values, and merit‑based progression with healthcare, 401k matching, and continuous improvement
• Enjoyable days – focus on career growth, mentoring, and community work during company time
• Balanced lives – flexible hours, work‑from‑home options, and work‑life balance support

Competitive total rewards package includes health and welfare benefits, tuition assistance, 401K savings, and employee assistance programs.

Base salary range: $150,000 – $195,000. Position may be eligible for performance‑based incentives.

Oliver Wyman is an equal opportunity employer. We are committed to diversity, equity, and inclusion.