Business Graduate Associate (Data & Analytics)

LSEG — Bengaluru, Karnataka

₹3–4 LPA (HireSetu estimate) · Entry level · Freshers eligible · Full-time · Apply by 10 Oct 2026

HireSetu listing reference 76c40d · employer requisition R0123974 — confirm requirements below, then apply on the employer site.

Quick answer: A 12-month graduate programme in LSEG's Data & Analytics division in Bengaluru, permanent from day one. Two things separate the applicants who get through: working SQL on multi-table datasets, and genuine interest in financial markets.

From LSEG's job posting

Join our Data & Analytics Division and help shape how data, technology and insight are turned into products and solutions that create value for our customers.

As we continue to embrace a product-led approach, we are looking for graduates who are curious about customers, data and technology and interested in understanding how these come together to solve problems and deliver meaningful outcomes.

From day one, you’ll work in a fast-paced, collaborative environment, developing your understanding of financial markets while building skills across data, analytics, AI, business intelligence and product management.

During the 12-month Graduate Programme, you will

  • Build foundational skills for your future career within Data & Analytics.
  • Develop your understanding of financial markets, customers and our business.
  • Learn how a product-led mindset connects customer needs, data and business outcomes.
  • Explore how data, analytics and AI can inform decisions and improve products and experiences.
  • Collaborate with colleagues across different teams to understand problems and develop solutions.
  • Participate in projects, professional development, CSR and volunteering opportunities.
  • Connect with our global Early Careers community.

Our graduates join on a permanent basis and will be aligned to Data & Analytics from day one.

What we're looking for

We're looking for curious, analytical and collaborative individuals who are excited by the opportunity to work at the intersection of data, technology, customers and products.

You'll stand out if you can demonstrate

  • An interest in product management and product-led ways of working.
  • Curiosity about customers and the ability to understand problems from a customer perspective.
  • An interest in Data Science, Data Analytics, AI or Business Intelligence.
  • The ability to use data and information to draw conclusions and solve problems.
  • Strong communication, collaboration and strategic thinking skills.
  • An interest in financial markets and how technology and data are shaping the industry.
  • Adaptability and resilience in a fast-paced environment.

We particularly welcome candidates from Data Science, Artificial Intelligence, Data Analytics, Business Analytics, Computer Science or related quantitative disciplines. While technical backgrounds are preferred, they are not essential where you can demonstrate strong interest and capability in data and product-led thinking.

Foundational understanding of financial markets, asset classes, and corporate finance.

Practical working knowledge of SQL for querying, filtering, and aggregating multi- table datasets. Introductory proficiency Python for data analysis.

Eligibility

You must have completed your studies in 2026, or be a final-year undergraduate or Master's student who will complete all course requirements before summer 2027.

Preferrable combination of Engineering + Finance background

Our recruitment process includes

  • Application submission
  • Immersive Online Assessment
  • Video Interview, exploring your strengths, motivation, customer thinking and interest in product-led ways of working
  • Assessment Centre, involving a range of exercises

We are interested not only in what you achieve, but how you achieve it, including how you understand customer needs, use data and evidence, collaborate with others and approach problems.

Applications are reviewed on a rolling basis and may close early, so we encourage you to apply as soon as possible.

Please review our Graduate Programme opportunities and submit one application only.

Text from LSEG's official job posting, formatted by HireSetu. The employer's own page is the final word on details.

HireSetu's note

The bar that filters applicants

Almost every applicant will arrive with a degree and some Python. SQL is what actually counts: joins, filters and aggregations across multi-table data, plus enough schema sense to work out which table holds the answer. Python only needs to be introductory, so put your preparation hours into querying and markets instead of models.

Engineering plus Finance is the preferred combination, which says plenty about the work: quantitative data on real instruments. Coming from computer science or analytics, you close that finance gap yourself. Asset classes, corporate finance basics, what moves a bond price.

A week in the division

You are aligned to Data & Analytics from day one and stay there. Expect to spend your hours answering questions with data: pulling and cleaning datasets, keeping a report or dashboard alive, sitting with product managers and customers to work out which problem is worth solving. The early months carry onboarding, the global early careers community, CSR and volunteering on top of project work.

Twelve months, then a permanent seat. Which team you land in depends on where you are placed.

Closer to product than the title suggests

Graduate titles with 'business' in them often mean internal reporting for a function. This one sits inside a division that builds products customers pay for, and the language around it is product management and product-led thinking, not a queue of reporting tickets. That puts you near decisions about what gets built and why.

Modelling is a smaller slice here than a data science associate role would give you. The daily questions are about customers, evidence and trade-offs.

Topics worth a few evenings

Window functions are worth learning beyond joins and GROUP BY; they show up constantly in analytics work. Pandas for light cleaning. On the finance side, be able to explain the main asset classes and what a benchmark index is for without reaching for notes.

Applications are reviewed as they arrive and can close early, and you are asked to submit one application only. Settle on the division you want before you send it.

Drafted with AI from LSEG's job posting and checked by Prashanth Jakkula before publishing. See our Editorial Policy.

How to apply

  1. Open LSEG's careers site with the Apply button.
  2. Create a Workday account for LSEG. Workday logins are separate for every company, so an account made for another employer won't work here.
  3. Upload your resume and check every auto-filled field; Workday often misreads dates and job titles.
  4. Answer the screening questions, submit, and look for the confirmation email from Workday.

Apply on LSEG's site

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