LSEG – Business Graduate Associate (Data & Analytics)

Job Description

London Stock Exchange Group (LSEG) is hiring Business Graduate Associates in Data & Analytics for its 12-month Graduate Programme in Bengaluru. This opportunity is designed for recent graduates and final-year students who are interested in the intersection of data, technology, financial markets, customers and product management. As a Business Graduate Associate, you will join the Data & Analytics division from the beginning and develop practical knowledge of how data and technology are transformed into products, insights and business solutions. The role provides exposure to areas such as data analytics, artificial intelligence, business intelligence, data science and product-led development, while also helping graduates understand how financial markets operate. Candidates will work in a collaborative environment where curiosity, analytical thinking, communication and problem-solving are important parts of day-to-day work.

During the graduate programme, associates will have opportunities to contribute to projects while developing a strong understanding of customer requirements and business challenges. The programme focuses on building foundational capabilities that can support a long-term career within LSEG's Data & Analytics organisation. Graduates will learn how a product-led mindset connects customer problems with data, technology and measurable business outcomes. They may collaborate with professionals from different functions to understand problems, examine available information, identify patterns and contribute to potential solutions. The position is particularly suitable for candidates who enjoy working with data and are interested in understanding how analytical insights can support better products and business decisions. Alongside project-based learning, participants will receive professional development opportunities and exposure to LSEG's global Early Careers community.

The role also provides an opportunity to combine technical and commercial knowledge. Candidates with backgrounds in Data Science, Artificial Intelligence, Data Analytics, Business Analytics, Computer Science, Engineering, Finance or related quantitative disciplines can bring relevant skills to the programme. A foundational understanding of financial markets, asset classes and corporate finance will be useful, while practical knowledge of SQL and introductory Python can help candidates work effectively with data. Associates are expected to approach problems using evidence and structured thinking, communicate their findings clearly and collaborate with colleagues across teams. The programme also values adaptability and resilience because graduates will work in a fast-paced environment where priorities, customer needs and business challenges can evolve. Successful graduates join LSEG on a permanent basis and remain aligned to the Data & Analytics division from day one.

Roles & Responsibilities

1. Support Data & Analytics Projects
   Participate in projects involving data, analytics, business intelligence, AI and product-related initiatives while developing practical workplace experience.
2. Understand Customer Requirements
   Study customer needs and business problems from a user perspective to help teams identify meaningful opportunities for products and data-driven solutions.
3. Analyse Business Data
   Work with available datasets and information to identify patterns, draw conclusions and support evidence-based business decisions.
4. Use SQL for Data Analysis
   Apply foundational SQL skills to query, filter and aggregate information from multi-table datasets while developing stronger data-handling capabilities.
5. Apply Python Fundamentals
   Use introductory Python knowledge for data analysis and gradually build practical programming skills relevant to analytics and business problem-solving.
6. Explore Product Management
   Develop an understanding of product-led ways of working and learn how customer requirements, data and technology can be connected to business outcomes.
7. Learn Financial Markets
   Build knowledge of financial markets, asset classes and corporate finance while understanding how technology and data influence the financial services industry.
8. Collaborate Across Teams
   Work with colleagues from different functions, communicate ideas clearly and contribute constructively to discussions, analysis and project activities.
9. Develop Data-Driven Insights
   Examine information logically and contribute insights that can help teams understand problems, evaluate alternatives and improve products or experiences.
10. Participate in Professional Development
    Take part in learning activities, professional development programmes, CSR initiatives, volunteering opportunities and Early Careers community events.
11. Demonstrate Strategic Thinking
    Approach business challenges with structured reasoning, curiosity and an understanding of how individual decisions can influence broader customer and organisational outcomes.
12. Adapt to Changing Priorities
    Demonstrate resilience and flexibility when working in a fast-paced environment with evolving customer expectations, technology and business requirements.

Requirements & Eligibility

1. Educational Background
   Candidates should be pursuing or have completed a degree in Data Science, Artificial Intelligence, Data Analytics, Business Analytics, Computer Science, Engineering, Finance or another relevant quantitative discipline.
2. 2026 Graduate Eligibility
   Applicants must have completed their studies in 2026 or be final-year undergraduate or Master's students who will complete all course requirements before summer 2027.
3. Engineering and Finance Interest
   An Engineering plus Finance background is preferable for this opportunity, particularly for candidates interested in combining technical knowledge with financial-market understanding.
4. SQL Knowledge
   Candidates should have a foundational practical understanding of SQL, including querying, filtering and aggregating data across multiple tables.
5. Python Fundamentals
   Introductory proficiency in Python for data analysis is expected, with the ability and willingness to develop stronger analytical programming skills.
6. Data & Analytics Interest
   Applicants should demonstrate genuine interest in Data Science, Data Analytics, Artificial Intelligence, Business Intelligence or related data-driven disciplines.
7. Product Mindset
   An interest in product management and product-led ways of working is valuable, particularly the ability to connect customer needs with data, technology and business outcomes.
8. Financial Markets Awareness
   Candidates should have a foundational understanding of financial markets, asset classes and corporate finance and be interested in how technology is transforming financial services.
9. Analytical & Problem-Solving Skills
   The ability to interpret information, use data as evidence, identify relationships and draw logical conclusions is important for success in the role.
10. Communication & Collaboration
    Strong communication, teamwork, strategic thinking, adaptability and resilience are important because associates will work with multiple teams in a fast-moving professional environment.

Recruitment Process

The LSEG Business Graduate Associate recruitment process is expected to include multiple stages designed to assess both technical potential and broader workplace capabilities:

• Application Submission – Candidates submit their application and relevant academic and professional information.
• Immersive Online Assessment – Applicants complete an online assessment designed to evaluate relevant skills and capabilities.
• Video Interview – Candidates discuss their strengths, motivation, customer-focused thinking and interest in product-led ways of working.
• Assessment Centre – Shortlisted applicants participate in a range of exercises designed to evaluate problem-solving, collaboration, communication and other relevant capabilities.

LSEG states that the recruitment process considers not only what candidates achieve, but also how they approach problems, understand customer needs, use evidence, collaborate and make decisions. Applications are reviewed on a rolling basis, so candidates are encouraged to apply early.

Expected Salary

The exact salary for the Business Graduate Associate (Data & Analytics) position is not specified in the supplied job posting. Based on current Bengaluru market estimates for LSEG-related graduate, analyst and data-oriented positions, candidates may reasonably expect an approximate package in the ₹6 lakh to ₹9 lakh per annum range, although the actual offer can vary depending on the role structure, candidate profile and compensation components.

Why This Graduate Opportunity Matters

The LSEG Business Graduate Associate programme is structured for candidates who want to build a career where data, technology, financial markets and business strategy overlap. Rather than focusing exclusively on a single technical discipline, the programme introduces graduates to several connected areas, including analytics, AI, business intelligence and product management.

The permanent nature of the programme also gives graduates an opportunity to build their career within LSEG's Data & Analytics organisation after completing the 12-month graduate programme. The combination of structured learning, project exposure, cross-team collaboration and financial-market knowledge can help participants develop a broad understanding of how data-driven products and solutions are created and improved.

About LSEG

London Stock Exchange Group (LSEG) is a global financial markets infrastructure and data provider. The organisation operates across financial markets, data and technology and aims to support financial stability, economic growth and customer outcomes.

LSEG has a global workforce and operates across multiple regions, bringing together expertise in financial markets, data, technology and related services. Its stated values include Integrity, Partnership, Excellence and Change, which guide its approach to collaboration, customer service and continuous improvement.

For graduates, the organisation provides exposure to an international working environment where technology and financial-market knowledge come together. The Data & Analytics division plays an important role in developing data-driven products, insights and solutions for customers.

🚨 Stop Scrolling – This Could Be Your Shortcut to Interviews

Most candidates apply to 100+ jobs and never hear back.
The real reason? They don’t know where recruiters are actually hiring from.

Our April Hiring PDF includes verified HR emails and hiring details from companies like:

Dentsu, IBM, HCL, PwC, LTIMindtree, Wipro, Cognizant, Deloitte, Capgemini, Amazon, TCS, Infosys, EPAM, EY, NTT Data, Tech Mahindra, Fractal, GlobalLogic, Coforge, UST and many more.

Inside you’ll find:
✔ 300+ Fresher Job Opportunities
✔ 2500+ Verified HR Emails & Contacts
✔ Direct Hiring + Consultancy Openings
✔ IT & Non-IT Roles

🔥 60+ students placed recently using these hiring leads

👉 Grab the April Hiring List Now: April Hiring PDF