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
We will count on you to:
- Identify opportunities which add value to the business and make the process more efficient.
- Have the ability to work with colleagues and stakeholders across levels, understand business objectives and make sure all analysis and findings are aligned to those business objectives.
- Invest in understand the core business including products, process, documents, and data points with the objective of identifying efficiency and value addition opportunities.
- Gather, analyze, and model data using analytical tools and techniques to develop business insights to drive decisions
- Design, develop, and maintain robust data pipelines for extracting, transforming, and loading (ETL) data from diverse sources.
- Automate data extraction, transformation, and loading (ETL) from various sources, including PDFs and APIs.
- As the operational scales up design and implement scalable data storage solutions and integrate them with existing systems.
- Develop scripts and applications to extract and process data from PDF documents using Python.
- Collaborate with data scientists and analysts to optimize data workflows and improve data accessibility.
- Write efficient, reusable, and testable code to support data processing needs.
- Utilize cloud platforms (AWS, Azure, Google Cloud) for data storage and processing.
- Perform data extraction from multiple data sources and ensure data integrity and accuracy.
- Utilize AI/ML models and tools, including Large Language Models (LLM) and Generative AI, to enhance data processing capabilities.
- Design scalable and reliable system architectures to support data-intensive applications.
- Implement and maintain security and data protection solutions.
- Conduct code reviews and provide mentorship to junior developers.
- Stay up-to-date with the latest technology trends and best practices in data engineering and cloud services.
- Develop dynamic dashboards that provide insights and visualization into performance relative to KPIs, projections, and historical performance.
- Use technical skills to gather and work with large volumes of data using the most suitable technology.
- Institutionalize data quality check mechanisms in the data gathering and analysis phases.
- Develop scalable solutions for automations of reports.
- Ability to lead initiatives and deliver results by engaging with cross-functional teams and resolving data ambiguity issues.
- Be responsible for the professional development of your projects and institute a succession plan.
What you need to have:
- Bachelor's degree in Engineering, Analytics, or a related field, MBA, Computer Applications, IT, Business Analytics, or any discipline.
- Proven experience of 8-12 years in Python development
- Proven experience with data automation and building data pipelines.
- Proven track record in building and maintaining data pipelines and ETL processes.
- Hands-on experience with AI/ML models and tools.
- Strong knowledge of Python libraries such as Pandas, NumPy, and PySpark, Camelot.
- Experience building application using LLM, vision and NLP models.
- Experience with cloud platforms (AWS, Azure, Google Cloud) and their data services.
- Proficiency in extracting data from various sources, including APIs and PDFs.
- Familiarity with database management systems (SQL and NoSQL databases).
- Experience in designing and implementing system architecture.
- Ability to operate in a multi layered technology architecture and shape the technology maturity of the organization.
- Solid understanding of software development best practices, including version control (Git), code reviews, and testing frameworks (PyTest, UnitTest).
- 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. Specify superior listening, verbal and written communication skills
- Excellent project management and organization skills
- Superlative stakeholder management skills – ability to positively influence stakeholders.
- Synthesis skills- Ability to connect the dots and answer the business question.
- Excellent problem-solving, structuring and critical-thinking skills.
- Ability to work independently and collaboratively in a fast-paced environment.
What makes you stand out
- Master's degree in Computer Science, Engineering, or related fields.
- Experience in working with large-scale data sets and real-time data processing.
- Familiarity with additional programming languages like Java, C++, or R.
- Strong problem-solving skills and ability to work in a fast-paced environment.
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 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.
