Lead Specialist - Data Analytics & Insight

Company:

Description:

Marsh is hiring for below position for Mumbai location.

Job Title : Lead Specialist- Data Analytics & Insights

What can you expect:

• Be a part of the team that is core to driving analytics for impactful business outcomes .

• A vibrant and collaborative community of professionals across capabilities such as data management, data analytics, data visualization, data science, business intelligence and many others.

• An open, inclusive and meritocratic environment with an emphasis on innovation and solving business problems.

• Collaborative approach to work, in order to work with global setup with multiple stakeholders.

• Be part of a multi-cultural team and working with multi-cultural teams

What is in it for you

• As a global leader in insurance broking and risk management, we are devoted to finding diverse individuals who are committed to the success of our clients and our organization.

• Joining us will provide a solid foundation for you to accelerate your career in the risk and insurance industry.

• You will join a team of talented professionals from across the globe which is dedicated to helping clients manage some of the world's most challenging and complex risks.

• We can promise you extraordinary challenges, extraordinary colleagues, and the opportunity to make a difference.

• Our rich history has created a client service culture that we believe is second to none. Our commitments to Diversity and Inclusion, Corporate Social Responsibility, and sustainability demonstrate our commitment to stand for what is right.

We will count on you to:

• Understanding of our business and business model in order to thoughtfully model and analyze data.

• Be extremely comfortable around large volumes of data.

• Have the ability to work with colleagues across levels, understand business objectives and make sure all analysis and findings are aligned to those business objectives.

• Assemble large, complex sets of data, Identifying, designing and implementing internal process improvements including re-designing infrastructure for greater scalability, optimizing data delivery, and automating manual processes 

• Gather, analyze and model data using Python to develop business insights to drive decisions.

• Support strategic decision making by providing actionable recommendations based on data analysis.

• Be extremely detail oriented and deliver error free outputs consistently

• Support strategic decision making by providing actionable recommendations based on data analysis.

What you need to have: 

• Bachelor's degree in Engineering, Analytics, or a related field, or a Master's degree in Statistics, Computer Applications, IT, Business Analytics, or any discipline.

• Proven experience of 4-5 years in data analysis, data visualization, and working with large data sets.

• Strong knowledge of statistical concepts and their application in data analysis.

• Proficiency in SQL and Python for data extraction and manipulation.

• Demonstrate specific experience in managing a database along with writing intermediate to complex SQL queries for data extraction.

• Possess strong data visualization abilities and experience with data visualization tools such as Tableau, Power BI, or Qlik Sense to effectively communicate insights from data

• Excellent problem-solving and critical-thinking skills.

• Strong attention to detail and ability to work with complex data sets.

• Effective communication skills to present findings and insights to both technical and non-technical stakeholders.

• Acute thinking skills: able to understand the business problem, and structure it to identify relevant dataset and answer through a strong visual storyboard.

• Synthesis skills- Ability to connect the dots and answer the business question.

• Ability to work independently and collaboratively in a fast-paced environment

What makes you stand out:

• A commercial sense to apply proportionality to the depth of analytics used versus desired output.

• Ability to take initiatives to strive for improvement in analytics techniques, process and output.

Marsh McLennan (NYSE: MMC) is the world’s leading professional services firm in the areas of risk, strategy and people. The Company’s 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. Marsh provides data-driven risk advisory services and insurance solutions to commercial and consumer clients. Guy Carpenter  develops advanced risk, reinsurance and capital strategies that help clients grow profitably and pursue emerging opportunities. Mercer  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. Oliver Wyman serves as a critical strategic, economic and brand advisor to private sector and governmental clients. For more information, visit marshmclennan.com, or 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.