Data Scientist

Oliver Wyman is seeking candidates for the following position based in the Pune/Mumbai/ Gurgaon office:

We are seeking an experienced Data Scientist to collaborate with cross-functional stakeholders and translate strategic business goals into impactful data science solutions. The ideal candidate will analyze complex datasets, build scalable machine learning models, and develop automated data pipelines to drive data-driven decision-making across the organization. This role requires strong technical expertise, business acumen, and the ability to work within enterprise environments adhering to data governance, security, and compliance standards.

Key Responsibilities:

• Partner with business groups and technology teams to understand strategic objectives and translate them into actionable data science projects aligned with enterprise goals.
• Analyze large volumes of structured and unstructured data to extract insights, assess data quality, and perform advanced data wrangling and feature engineering.
• Design, develop, and implement efficient, scalable, and maintainable code for data manipulation and machine learning model development using Python (Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch) or R.
• Develop and maintain automated ETL pipelines leveraging cloud-based platforms such as Databricks, AWS S3, Athena, Glue, or equivalent enterprise data platforms.
• Utilize GenAI and ChatGPT APIs to automate data ingestion and processing workflows; familiarity with large language models (LLM), retrieval-augmented generation (RAG), Power BI, and Tableau is a plus.
• Build and integrate RESTful APIs to enable seamless and secure data exchange between internal systems and external partners.
• Create and maintain automation scripts for data extraction, transformation, and reporting using Python and other scripting languages.
• Write optimized SQL queries and manage enterprise-grade database systems; experience with data warehousing solutions such as Redshift, Snowflake, or Azure Synapse is required.
• Demonstrate expertise in data modeling, transformation, storytelling, and visualization using Power BI, Tableau, or similar BI tools.
• Communicate complex technical insights and analyses clearly and concisely to both technical and non-technical stakeholders, supporting data-driven decision-making.
• Apply machine learning, statistical modeling, and time-series forecasting techniques (classification, regression, clustering, random forest, gradient boosting, etc.) to build, calibrate, and validate predictive models.
• Deliver end-to-end data pipelines and deploy machine learning models in production environments following enterprise best practices for scalability, monitoring, and governance.
• Ensure compliance with data privacy, security policies, and regulatory requirements (e.g., GDPR, HIPAA) during data handling and model deployment.
• Collaborate with data engineering, IT, and security teams to ensure robust data infrastructure and governance frameworks.

Required Qualifications:

• Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, Mathematics, or a related quantitative field.
• 4+ years of hands-on experience with cloud-based data science and engineering technologies, including platforms like Databricks, AWS S3, Athena, Glue, or comparable enterprise cloud services.
• Strong programming skills in Python with expertise in libraries such as Pandas, NumPy, Scikit-learn, TensorFlow, or PyTorch.
• Proficient in SQL and experienced with enterprise database management and data warehousing technologies (e.g., Databricks, Redshift, Snowflake, Azure Synapse).
• Experience designing and developing automated data pipelines and workflows; familiarity with Git, CI/CD, and DevOps principles.
• Proven ability to design, implement, and deploy machine learning models and data workflows in production environments.
• Strong analytical, problem-solving, and communication skills, with the ability to translate complex technical concepts for diverse audiences.
• Experience working in enterprise environments with strict data governance, security, and compliance requirements.

Preferred Skills:

• Experience with GenAI, ChatGPT API integration, and working knowledge of large language models (LLM) and retrieval-augmented generation (RAG).
• Proficiency in data visualization tools such as Power BI, Tableau, or equivalent.
• Familiarity with REST API development and integration.
• Knowledge of time-series forecasting and advanced machine learning algorithms including ensemble methods and deep learning.
• Exposure to containerization (Docker), orchestration (Kubernetes), and cloud ML platforms (e.g., Azure ML, Databricks AI Platform).
• Experience in agile project delivery and collaborative team environments.

About Oliver Wyman:

Oliver Wyman is a global leader in management consulting. With offices in 70 cities across 30 countries, Oliver Wyman combines deep industry knowledge with specialized expertise in strategy, operations, risk management, and organization transformation. The firm has more than 7,000 professionals around the world who work with clients to optimize their business, improve their operations and risk profile, and accelerate their organizational performance to seize the most attractive opportunities. Oliver Wyman is a business of Marsh McLennan [NYSE: MMC]. For more information, visit www.oliverwyman.com. Follow Oliver Wyman on X @OliverWyman.

Marsh McLennan is committed to embracing a diverse, inclusive and flexible work environment. We aim to attract and retain the best people and embrace diversity of age, background, caste, disability, ethnic origin, family duties, gender orientation or expression, gender reassignment, 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 McLennan 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 McLennan 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.