Oliver Wyman - Senior Data Scientist

Marsh McLennan • Bunnell, FL

1d • Hybrid

About The Position

Oliver Wyman is a global leader in management consulting. With offices in 50+ cities across 30 countries, Oliver Wyman combines deep industry knowledge with specialized expertise in strategy, finance, operations, technology, risk management, and organizational transformation. Our 4000+ professionals help clients optimize their business, improve their IT, operations, and risk profile, and accelerate their organizational performance to seize the most attractive opportunities. Our professionals see what others don't, challenge conventional thinking, and consistently deliver innovative, customized solutions. As a result, we have a tangible impact on clients’ top and bottom lines. Our clients are the 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 the power of digital technology with deep industry expertise to tackle disruption and create impact. By building strong capabilities and culture, we accelerate and embed digital transformation. Our people co-create and grow customer-focused solutions that win. We modernize technology and harness value from data and analytics. We build resilience so our clients are ready for tomorrow’s risks and can optimize operations for the future. Above all, we work collaboratively with our 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. You’ll be working with varied and diverse teams to deliver unique and unprecedented products across industries. As a Data Scientist, you are responsible for supporting technical projects, including data engineering, model selection and design, and infrastructure deployment in both internal and client environments. We want and expect our people to develop deep expertise in a particular industry (financial services, health and life sciences, etc.), but you should be comfortable developing methods and selecting approaches based on a combination of first principles thinking, curiosity, and your pre-built foundations of software engineering and development. As a Data Scientist, you will work alongside Oliver Wyman partners in the Quotient within our Performance Transformation practice and other practice groups, engage directly with clients to understand their business challenges, and craft appropriate solutions to be delivered through collaboration with other OW Digital specialists and consultants.

Requirements

• Technical background in computer science, data science, machine learning, artificial intelligence, statistics, or other quantitative and computational science
• Track record of designing and deploying 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.)
• Developing Generative AI and Agentic AI solutions, leveraging patterns such as Retrieval Augmented Generation (RAG), multi-agent frameworks and performance evaluation.
• 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.
• Knowledge of one or more of the key generative AI frameworks ackages, including but not limited to: OpenAI, Anthropic, Strands Agents, Langchain, 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 the major ideas in 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 – e.g., Statistics, Linear Algebra and Vector Calculus
• 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

Nice To Haves

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

Responsibilities

• 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

Benefits

• Flat organizational structures, resolute I&D values, and a commitment to rewarding good work make for a progression path truly based on merit.
• A menu of healthcare options, 401k matching, and a culture of continuous improvement means your work gets more rewarding over time.
• This commitment also leads to opportunities for social impact and community work on company time.
• We’ll work with you to accommodate your personal life with flexible hours and the ability to work from home.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 5,001-10,000 employees