Senior Manager - Data Science

Marsh is seeking candidates for the following position based in the Mumbai office.

Senior Manager - Data Science

What can you expect?

• This position is for an individual contributor in Data Science, who will develop and implement models using leading-edge techniques in machine learning, predictive modeling, artificial intelligence, and natural language processing as applied in commercial insurance and risk management.

  
  

• This position consults with clients and colleagues on complex financial and statistical analyses, and develops approaches for new, market-leading analytics-based tools.

  
  

What is in it for you?

• Holidays (As Per the location)

  
  

• Shared Transport (Provided the address falls in service zone)

  
  

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 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

  
  

What you need to have?

• Master’s Degree in Math, Statistics, Data Science, Actuarial Science or related field

  
  

• Expert statistical modeling knowledge, including familiarity with machine learning techniques

  
  

• Ability to face difficult and sometimes complex problems

  
  

• 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, TensorFlow, SQL, and PyTorch

  
  

• 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 NLP and computer vision

  
  

• Experience of building data visualization in Plotly/Dash/D3.js

  
  

• Hands on experience with stochastic or econometric modelling

  
  

Marsh is the world’s leading insurance broker and risk adviser. With more than 45,000 colleagues advising clients in over 130 countries, Marsh serves commercial and individual clients with data-driven risk solutions and advisory services. Marsh is a business of Marsh McLennan (NYSE: MMC), the world’s leading professional services firm in the areas of risk, strategy and people. With annual revenue of $23 billion, Marsh McLennan helps clients navigate an increasingly dynamic and complex environment through four market-leading businesses: Marsh, Guy Carpenter, Mercer, and Oliver Wyman. For more information, visit marshmclennan.com, follow us 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.