Lead AI Specialist - Insurance Operations

Lead Specialist - Insurance Operations (AI Specialist)

Company:

Marsh

Description:

We are seeking a talented individual to join our Insurance Operations 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.

Lead Specialist – Insurance Operations (Grade D1)

We are seeking a motivated and innovative AI Specialist to join our insurance operations team. This role offers a unique opportunity to apply AI knowledge to identify new areas for automation and improvement, support upskilling initiatives, and enhance operational efficiency across the entire value chain. This colleague will work closely with cross-functional value streams to drive AI adoption and process transformation.

We will count on you to:

• Identify and analyze opportunities to apply AI and machine learning techniques to improve operational processes end-to-end.

• Collaborate with operations teams to understand workflows and pain points, proposing AI-driven solutions to enhance efficiency and accuracy.

• Support the design and delivery of training programs to upskill employees on AI tools, technologies, and best practices.

• Assist in developing and maintaining AI models, dashboards, and automation scripts to support day-to-day operations.

• Monitor and evaluate the impact of AI initiatives on process performance and suggest continuous improvements.

• Work with data teams to gather, clean, and prepare data necessary for AI model development and validation.

• Stay updated with the latest AI trends and technologies relevant to insurance operations and share insights with the team.

• Support change management efforts by communicating AI benefits and fostering a culture of innovation within the operations team.

What you need to have:     

• Master’s degree in Computer Science, Data Science, Artificial Intelligence, Engineering, or Management.

• Strong foundational knowledge of AI, machine learning, and data analytics concepts.

• 5 + years of experience

• Basic programming skills in Python, R, or similar languages.

• Familiarity with AI/ML frameworks and tools (e.g., TensorFlow, scikit-learn) is a plus.

• Excellent problem-solving skills and a proactive mindset.

• Strong communication skills with the ability to explain technical concepts to non-technical stakeholders.

• Eagerness to learn, collaborate, and contribute in a fast-paced operational environment.

• Prior internship or project experience in AI or process improvement is desirable but not mandatory.

What makes you stand out:

• Adaptable communicator, facilitator, influencer and problem solver

• Good relationship skills, Proven ability to work on own initiative as well as in a team 

• Ability to multi-task and prioritize time effectively

• CII Certification

• Proven Insurance domain knowledge in the entire General Insurance lifecycle

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 corporate.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.

Marsh Risk is a business of Marsh (NYSE: MRSH), 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 about Marsh Risk, 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.

Experience Level

Senior Level