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Oliver Wyman is a global leader in management consulting. With offices in over 50 cities across 30 countries, we combine deep industry knowledge with expertise in strategy, finance, operations, technology, risk management and organizational transformation. Our 4,000+ professionals help clients optimize their business, improve IT, operations, and risk profiles, and accelerate performance to seize attractive opportunities. We deliver innovative, customized solutions to CEOs and executive teams of the top Global 1000 companies.

At Oliver Wyman Digital we partner with clients to deliver breakthrough outcomes for their toughest digital challenges. We blend digital technology with industry expertise to tackle disruption, create impact, modernize technology, harness value from data and analytics, and build resilience for tomorrow’s risks. We work collaboratively with clients’ leaders, employees, stakeholders and customers to jointly define, design, and achieve lasting results.

Our clients drive our projects, and no two OW Digital projects are the same. As Lead Data Scientist you will primarily manage technical projects, including data engineering, model selection/design, and infrastructure deployment in both internal and client environments. You should be comfortable developing methods and selecting approaches based on first principles thinking, curiosity, and a strong foundation in software engineering, while delivering solutions that meet business needs.

• Explore data, build models, and evaluate solution performance to resolve core business problems
• Explain, refine, and collaborate with stakeholders through the model‑building journey
• Stay current on domain state‑of‑the‑art techniques and emerging modeling and data‑engineering methodologies
• Advocate best practices in modeling, code hygiene, and data engineering
• Lead the development of proprietary statistical techniques, algorithms, or analytical tools on projects and asset development
• Work with Partners and Principals to shape proposals that leverage our data science and engineering capabilities

• Technical background in computer science, data science, machine learning, artificial intelligence, statistics, or related quantitative science
• Compelling track record of designing and deploying large‑scale technical solutions, delivering tangible, ongoing value:
  • Built and deployed robust, complex production systems implementing modern data science methods at scale, including supervised and unsupervised learning
  • Leveraged cloud‑based infrastructure‑as‑code (e.g., CloudFormation, Bicep, Terraform) to enable rapid, repeatable deployment across environments
  • Demonstrated poise in time‑boxed environments, making rapid design decisions
• Fluency in modern programming languages for data science (≥Python), covering the full ML lifecycle (data storage, feature engineering, model persistence, inference, observability) using open‑source libraries
  • Knowledge of one or more machine‑learning frameworks (Scikit‑Learn, TensorFlow, PyTorch, MxNet, ONNX, etc.)
  • Familiarity with modern storage and computational frameworks, with cloud‑first considerations for Azure and AWS
  • History of side projects or open‑source contributions is valued but not required
• Solid theoretical grounding in the mathematical core of data science
  • Deep understanding of modeling or analytical techniques (Bayesian modeling, time‑series forecasting, etc.)
  • Fluency in statistics, linear algebra, and vector calculus
• Experience presenting at high‑impact data science conferences and active connections to the data science community are highly valued
• Interest or background in financial services, capital markets, healthcare, life sciences, consumer, retail, energy, or transportation industries

• Undergraduate or advanced degree from a top academic program
• Passion for technology and solving problems
• Pragmatic approach to solutioning and delivery
• Excellent communication skills, both verbal and written
• Commitment to creating impactful solutions that solve client problems
• Ability to work fluidly and respectfully with a talented team
• Willingness to travel for client and internal stakeholder meetings

• Rewarding work – Reputation for high quality work and collaboration with major brands on exciting projects, supported by a culture of recognition.
• Progressive employment – Flat structure, strong I&D values, and advancement based on merit, with health benefits, a 401(k) match, and continuous improvement.
• Enjoyable days – Commitment to career development, mentoring, and opportunities for social impact during company time.
• Balanced lives – Support for flexible hours and work-from-home options to achieve work‑life balance.

We offer a competitive total rewards package which includes health and welfare benefits, tuition assistance, 401(k) savings, and employee assistance programs.

The applicability base salary range for this role is $150,000 to $195,000. Base pay will be determined based on experience, skills, location, certifications, and education, and any applicable minimum wage requirements. The position may also be eligible for performance‑based incentives.

Oliver Wyman is an equal opportunity employer. Our commitment to diversity is genuine, deep, and growing. We are not perfect, but we are working hard to make our teams balanced, representative and diverse.