Manager - Data Science

We are seeking a talented individual to join our Data Science team at Marsh. This role will be based in Mumbai. This is a hybrid role that has a requirement of working at least three days a week in the office.

Senior Manager - Data Science (AI - CoE)

This role at Knowledge Services aims to provide colleagues with an exposure towards key risks faced by businesses and utilize Artificial intelligence to manage, transfer or mitigate them. Incumbent is expected to be an expert of Generative AI (OpenAI API's), Prompt Engineering, Data Science algorithms, Business Analytics and Data Manipulation. Incumbent will also have an opportunity to contribute to cutting edge analytics platform and products. Expertise in Python is a must. Experience with Insurance or Banking industry is a plus.

This position is for an individual contributor in AI and Data Science, who will develop and implement leading-edge techniques in artificial intelligence, machine learning, predictive modeling, 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 AI-based tools.

We will count on you to

• Understand and refine the Math and Statistics behind the complex AI models
• Build AI and machine learning algorithms based on the business ask
• Keep up pace with new trends in the AI world
• Mine and analyze data to drive optimization and implement business strategies
• Deploy API's on the cloud platforms by understanding the technical ask
• Develop statistical custom data models and algorithms from scratch to enhance current value proposition and new product development

What you need to have:

• Develops solutions based on Large Language Models, Advanced transformers, Advanced deep learning/Neural networks models
• Expertise in image based advanced models, Object detection, Video/Image processing, multimodal RAG's and other image and video models
• Develops and deploys API based business solutions on AWS platforms
• Coordinates with technology colleagues within and outside the team for support, manage, enhance and retrains deployed models
• Keeps pace with the fast-evolving world of AI, large language models and other type of AI solutions in the market and able to apply research level knowledge to benefit Marsh advisory businesses
• Designs, develops and contributes to Data architecture for complex enterprise level applications
• Deploys solutions on AWS cloud platforms   
• Understands business problems to create an approach that starts with determining structured and unstructured data needs and availability, builds AI/ML models, and finalizes with results that unlock insight for clients/colleagues, deploy these solutions on web framework and enterprise wide platforms
• 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
• Coaches team members on the delivery of AI-based tools and analyses and presentation of findings
• Master's Degree in Engineering, Computer Science, Data Science or related field
• 7+ years of experience in the field of Data Science, AI research or similar fields
• Expert Data Scientist, including expertise with AI and machine learning model building
• Ability to influence others within and outside of the job function regarding approach and procedures
• Superior detail orientation, excellent communication and interpersonal skills
• Expertise of modern programming languages such as Python, including NumPy, Keras, TensorFlow, SQL, and PyTorch etc
• Familiar with Hugging face and is library of models

What makes you stand out?

• Building, training and deploying advanced models from the scratch to the production
• Business impact with AI models
• Understanding of insurance and risk management
• Knowledge and demonstrated experience of advance AI concepts like training language, voice, image or computer vision models  
• Experience of building data visualization in
• Hands on experience with stochastic or econometric modelling

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, a business of Marsh McLennan (NYSE: MMC), is the world's top insurance broker and risk advisor. Marsh McLennan is a global leader in risk, strategy and people, advising clients in 130 countries across four businesses: Marsh, Guy Carpenter, Mercer and Oliver Wyman. With annual revenue of $24 billion and more than 90,000 colleagues, Marsh McLennan helps build the confidence to thrive through the power of perspective. For more information, visit , or follow on LinkedIn and X.

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.