Lead Specialist - Data Science

Company:

Marsh

Description:

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

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:

• Explore and understand business nuances and help drive business strategies
• Mine and analyze data to drive optimization and implement business strategies
• Build AI and machine learning algorithms based on the business ask
• 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
• Conduct research on the client’s risk areas and prepare a point of view for consulting and apply AI expertise to solve client problems

What you need to have: 

• Master’s Degree in Engineering, Computer Science, Data Science, Actuarial Science or related field
• 6+ years of experience in the field of Data Science, AI research or similar fields
• Expert Data Scientist, including familiarity with AI and machine learning techniques
• Ability to influence others within and outside of the job function regarding approach and procedures
• Ability to develop strong internal/external client oriented solutions
• Superior detail orientation, excellent communication and interpersonal skills
• Knowledge of modern programming languages such as Python, including NumPy, Keras, TensorFlow, SQL, and PyTorch, Streamlit, Taipy etc.
• R or VBA may be helpful but not required

What makes you stand out?

• 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 Plotly/Dash/D3.js
• 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 marsh.com, 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.