Company:

Oliver Wyman

Description:

The Opportunity:

The Data Scientist is a Data Scientist with strong data science, statistical modelling, and machine learning expertise with practical software engineering skills to build data-driven products. This role is responsible for turning complex data into actionable insights and deployable models that enable users to operationalize analytics in meaningful ways.

Key Responsibilities:

• Partner with stakeholders to identify high-impact opportunities where data science can improve decision-making, processes, and business outcomes.
• Explore, clean, and transform structured and unstructured data; assess data quality, bias, and fitness-for-purpose.
• Develop and validate statistical and machine learning models (e.g., regression/classification, clustering, time series, etc.) and quantify uncertainty.
• Translate model results into clear narratives and recommendations; communicate insights to technical and non-technical audiences
• Create reusable data science assets (feature pipelines, model training/inference code, evaluation frameworks) with emphasis on reliability and maintainability.

Experience Required:

• Bachelor’s degree in Computer Science, Statistics, Mathematics, Data Science, Engineering, or a related quantitative field (or equivalent practical experience with demonstrable projects).
• 3+ years of professional experience applying data science/advanced analytics and delivering outcomes in real-world settings.
• Strong Python experience for data analysis and modeling
• Solid foundation in statistics (hypothesis testing, experimental design, regression, model evaluation, sampling/selection bias).
• Hands-on experience with SQL plus familiarity with NoSQL databases (e.g., MongoDB) and Databricks.
• Experience operationalizing analytics: reproducible pipelines, model packaging, deployment patterns, and monitoring.
• Comfortable with Git, CI/CD concepts, and Agile collaboration.

Preferred (Good to Have)

• Experience with modern ML libraries and workflows (e.g., scikit-learn, XGBoost/LightGBM, Py Torch/Tensor Flow; MLflow or similar).
• Experience with Databricks for ML.

Skills and Attributes:

• Excellent problem-solving and critical thinking skills required
• Able to frame ambiguous questions into testable hypotheses and measurable outcomes.
• Strong spirit of innovation, self-starter, independent, and with ability to come up with solutions to meet business problems
• Self-motivated with ability to work independently while also enjoying collaboration with cross-functional teams and other analysts
• Strong desire to learn new skills and pass knowledge acquired onto others
• Strong relationship building skills and ability to build alignment among customers and key stakeholders with demonstrated experience influencing without authority
• Ability to work effectively in a fast paced, deadline driven, highly dynamic atmosphere and react quickly to changes and shifting priorities.
• Effective communication skills and ability to translate numbers into a story
• Attention to detail and user-centric approach

Oliver Wyman is a business of Marsh (NYSE: MRSH), a global leader in risk, reinsurance and capital, people and investments, and management consulting, advising clients in 130 countries. With annual revenue of over $27 billion and more than 95,000 colleagues, Marsh helps build the confidence to thrive through the power of perspective. For more information, visit oliverwyman.com, or follow us on LinkedIn and X.

Marsh is committed to creating a diverse, inclusive and flexible work environment. We aim to attract and retain the best people and embrace diversity of age, background, disability, ethnic origin, family duties, gender orientation or expression, marital status, nationality, parental status, personal or social status, political affiliation, race, religion and beliefs, sex/gender, sexual orientation or expression, skin color, or any other characteristic protected by applicable law.

Marsh is committed to hybrid work, which includes the flexibility of working remotely and the collaboration, connections and professional development benefits of working together in the office. All Marsh colleagues are expected to be in their local office or working onsite with clients at least three days per week. Office-based teams will identify at least one “anchor day” per week on which their full team will be together in person.