Senior Engineer - Data Science

AI in this role

Develop and implement artificial intelligence, machine learning, and NLP techniques for commercial insurance and risk management.

pythonpandasnumpymatplotlibstreamlitpower-bicapital-iqfactivathomson-one

nlpai-researchmachine-learningnatural-language-processingpredictive-modellingstatistical-analysisdata-mining

Company:

Marsh Risk

Description:

Senior Engineer - Data Science

This position is for an individual contributor in Data Science, who will develop and implement leading-edge techniques in artificial intelligence, machine learning, predictive modelling, and natural language processing as applied in commercial insurance and risk management. This position consults with senior colleagues on complex financial and statistical analyses, and develops approaches for new, market-leading tools.

Core Responsibilities:

• Develops modelling approaches for implementing new, market-leading analytics-based tools to understand and address risk

• Understands business problems to create an approach that starts with determining structured and unstructured data needs and availability, builds Machine Learning models, and finalizes with results that unlock insight for clients and colleagues

• Demonstrates skill in advanced statistical analysis, data mining, and/or research techniques, combined with broader awareness of the business and ongoing research, while functioning in a collaborative role with the Data Science team and across the wider organization

• Stays current with ongoing research in the field and brings new approaches to the team

• Serves as an internal expert resource and champion for data science within Marsh.

We will count on you to:

• Hands on expertise in Python and Data related packages such as pandas, numpy, matplotlib, streamlit etc.

• Hands on expertise in Power BI.

• Build machine learning algorithms based on the business ask

• Deploy API on the platform by understanding the technical ask

• Develop statistical custom data models and algorithms from scratch to enhance current value proposition and new product development

• Utilize risk models related to Time Series Forecasting, Clustering, GLM/Regression, Boosting, Trees, etc.

• Use advanced analytics to augment consulting deliverables with data backed outputs

• Conduct research on the client’s risk areas and prepare a point of view for consulting.

• Well versed with key research tools such as Capital IQ, Factiva, Thomson One, etc.

What you need to have:

• Bachelors Degree in Engineering, Computer Science, Data Science, or related fields

• 0-2 year of experience in the field of Data Science, AI research or similar fields

• Ability to develop strong internal/external client-oriented solutions

• Superior detail orientation, excellent communication and interpersonal skills

• Hands on expertise of modern programming languages such as Python and SQL

• Understanding Risk modelling and inferential statistics.

• Knowledge of insurance contracts and risk business in general is a plus

What makes you stand out:

• Understanding of insurance and risk management

• Experience of building data visualization in MS-excel/PowerBI

Why join our team:

• We help you be your best through professional development opportunities, interesting work and supportive leaders.

• We foster a vibrant and inclusive culture where you can work with talented colleagues to create new solutions and have impact for colleagues, clients and communities.

• Our scale enables us to provide a range of career opportunities, as well as benefits and rewards to enhance your well-being.

Marsh (NYSE: MRSH) is 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 marsh.com, or follow us on LinkedIn and X.

Marsh 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 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.

How we rate this

Senior Engineer - Data Science at Marsh McLennan rates 90 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.

Key facts

Senior Engineer - Data Science is an open job at Marsh McLennan.
Level rates this role AI Level 4 of 4: Builds AI.
The role is based in Pune - Business Bay.
The job was posted on October 6, 2026.
Seniority: senior.
Applications are handled by Marsh McLennan. Apply on Marsh McLennan

Prepare for this job

A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.

Skills and AI tools this role asks for

NLPAI ResearchMachine LearningNatural Language ProcessingPredictive ModellingStatistical AnalysisData MiningPython

Questions you could be asked

What NLP problem have you worked on, and how did you measure whether it actually worked?
Tell me about a research question you investigated. What did you find?
Tell me about a project where machine learning was part of your work. What did you do?
Tell me about a project where natural language processing was part of your work. What did you do?
Tell me about a project where predictive modelling was part of your work. What did you do?

Adapt your resume

List these exact terms on your resume: NLP, AI Research, Machine Learning, Natural Language Processing, and Predictive Modelling. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
Lead with what you built, trained or shipped — this role is judged on the AI system itself, not the tools around it.

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