Job Description

Company: MarshDescription:Marsh McLennan Global Services is seeking candidates for the following position based in the Mumbai office:Lead Specialist - Data ScienceMMGS is a global knowledge center for Marsh McLennan and houses teams, which work closely with the colleagues across various operating units and locations. The Knowledge Services function under MMGS aims to provide specialized services in the domain of Research, Consulting, Data Analytics, Data Science, Actuarial and Design.What can you expect?

• Understanding of developing solutions based on OpenAI API's and other proprietary/open-source LLMs, leveraging their expertise in natural language processing and machine learning.
• Develops and deploys API-based business solutions on AWS platforms, ensuring scalability, reliability, and security.
• Collaborates with technology colleagues within and outside the team to provide support, manage, enhance, and retrain deployed models.
• Stays updated with the latest advancements in AI, large language models, and other AI solutions in the market, and applies research-level knowledge to benefit Marsh advisory businesses.
• Contributes to the design and development of data architecture for complex enterprise-level applications, ensuring efficient data storage, retrieval, and processing.
• Contributes to the design and development of data pipelines involving MongoDB, S3 buckets, data lakes, etc., ensuring seamless data flow and integration.
• Deploys solutions on AWS cloud platforms, leveraging cloud-native services and infrastructure.
• Understands business problems to create an approach that starts with determining structured and unstructured data needs and availability, builds AI/ML models, and delivers actionable insights to clients and colleagues. Deploys these solutions on web frameworks and enterprise-wide platforms.
• Demonstrates proficiency in statistical analysis, and data mining, while collaborating with the Data Science team and other stakeholders.

What's in it for you?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 APIs), 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

• 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 APIs 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 clients risk areas and prepare a point of view for consulting and apply AI expertise to solve client problems

What you need to have?

• Bachelors degree in engineering, Computer Science, Data Science, Actuarial Science or related field
• Data Scientist, including familiarity with AI and machine learning techniques
• Ability to develop strong internal/external client oriented solutions
• Superior detail orientation, excellent communication and interpersonal skills
• Knowledge of programming languages such as Python, including NumPy, Keras, TensorFlow, SQL, and PyTorch etc

What makes you stand out?

• Understanding of insurance and risk management
• Knowledge and demonstrated experience of AI concepts like training language models, voice models, image models, computer vision models
• Experience of building data visualization in Plotly/Dash/D3.js
• Hands on experience with stochastic or econometric modelling

(NYSE: MMC) is the worlds leading professional services firm in the areas of risk, strategy and people. The Companys more than 85,000 colleagues advise clients in over 130 countries. With annual revenue of $23 billion, Marsh McLennan helps clients navigate an increasingly dynamic and complex environment through four market-leading businesses. data-driven risk advisory services and insurance solutions to commercial and consumer clients. develops advanced risk, reinsurance and capital strategies that help clients grow profitably and pursue emerging opportunities. delivers advice and technology-driven solutions that help organizations redefine the world of work, reshape retirement and investment outcomes, and unlock health and well being for a changing workforce. serves as a critical strategic, economic and brand advisor to private sector and governmental clients. For more information, visit , or follow us on and .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.

Marsh McLennan