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

About the role

As a Lead Data Scientist at Oliver Wyman Digital, you will manage technical projects spanning data engineering, model selection and design, and infrastructure deployment across internal and client environments. You will develop deep expertise in a particular industry (e.g., financial services, health and life sciences) while applying first-principles thinking and software engineering foundations to craft solutions. You will collaborate with Oliver Wyman partners and clients to understand business challenges, co-create solutions, and deliver impact through collaboration with OW Digital specialists and consultants.

Responsibilities

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

Your Experience & Qualifications

You are a well-rounded technologist with a strong technical background in computer science, data science, machine learning, artificial intelligence, statistics, or other quantitative and computational sciences, and a 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, 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 consequential design decisions may need to be made and acted upon rapidly
• Fluency in modern programming languages for data science (at least Python) covering the full ML lifecycle (data storage, feature engineering, model persistence, model inference, and observability) using open-source libraries
• 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
• Solid theoretical grounding in the mathematical core of major data science ideas, including deep understanding of a class of modeling or analytical techniques (e.g., Bayesian modeling, time-series forecasting, etc.) and 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 or background in Financial Services and 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 clients’ problems
• The ability to work fluidly and respectfully with a talented team
• Willingness to travel for targeted client and/or internal stakeholder meetings

Our Values & Culture

We are serious about making OW Digital a rewarding, enjoyable, and balanced place to work. Rewarding work includes high-quality projects with major brands, recognition, and support. Progressive employment features flat structures, strong I&D values, and merit-based progression. Enjoyable days are supported by mentorship, development, and community work on company time. Balanced lives are supported with flexible hours and remote work options.