About Value Research

Value Research is an independent investment research firm founded in 1990. We began with equity research, with a report on PSU disinvestment, and have since built Indias most widely used mutual fund and stock research platform. Our work reaches millions of investors through Value Research Online, the monthly magazines Mutual Fund Insight and Wealth Insight, and our SEBI-registered advisory services.

We are paid by our readers, not by the companies we cover. That independence is the whole product.

Role overview The quant team builds the scoring frameworks and ratings that sit underneath our stock research and our advisory services. This role owns the method: what a score is trying to measure, why those inputs and not others, how we know it works, and what it is not entitled to claim.

That is a research job with a solid empirical discipline, not a modelling job in the abstract. Our frameworks are read by investors who act on them, so a score has to survive two tests that pure optimisation does not care about. It must hold up out of sample, and it must be explicable - to an analyst who will argue with it, and to a reader who deserves to know why their holding was marked down.

One thing to be clear about up front. We are long-term fundamental investors. The work here is measuring business quality, financial health and valuation over years, using reported accounts as the primary raw material. It is not signal-chasing, not high frequency, and not a search for edges that decay in a week. If that is the work you want, this is the wrong desk.

You will not be building the plumbing. A quant developer owns the pipelines, extraction and tooling, and you will specify what you need from them. But you are expected to prototype your own ideas, in code, without waiting for anyone.

Key Responsibilities

Design, test and maintain quantitative frameworks that score listed companies on business quality, financial health and valuation.





Turn the investment reasoning of experienced analysts into rules that can be computed, tested and defended - and be honest about what does not survive that translation.

Design and interpret backtests. Separate a robust result from an artefact of the sample, and say which one you are looking at.

Investigate why a framework produced a particular output: attribution, sensitivity, and the cases where it disagrees with an analyst who is probably right.

Specify the data, definitions and validation rules your work depends on, and work with the developer on implementation rather than around them.

Stress-test frameworks against awkward real companies - loss-making, cyclical, recently restructured, financial sector - rather than against a comfortable sample.

Document methodology clearly enough that a colleague can audit it and a reader can understand it, and support the writing that explains our method publicly.

Work within the review and record-keeping standards that regulated research requires.

Qualification and Experience

Graduate in statistics, mathematics, economics, finance, engineering, or any discipline paired with real quantitative ability.

Statistics understood rather than recited: distributions, dispersion, regression and the assumptions it rests on, correlation against causation, and the difference between statistically significant and actually important.

Knows why most impressive backrests are wrong - overfitting, lookahead, survivorship, and testing enough hypotheses to find something by accident.

Python and pandas at the level needed to prototype your own analysis end to end, without handing it to someone else first.





Can read a profit and loss statement, a balance sheet and a cash flow statement, and has some instinct for where accounting numbers mislead.

Writes clearly. If you cannot explain a model to someone who does not code, you cannot ship it here.

Genuine curiosity about how businesses make money, and the honesty to say when you do not know something.

Good to Have

Familiarity with the factor and value-investing literature, and a view on which parts of it have held up.

Event studies, cross-sectional testing, or portfolio construction experience.

SQL, stats models, scikit-learn, or R.

Exposure to Indian company and market data, and the ways it is routinely messy.

Research you can show us - a dissertation, a notebook, a blog, a competition entry. Published anywhere, or nowhere.

NISM Series XV, Research Analyst certification, or progress towards CFA or CA. We will support you in obtaining certification.

What we offer

Ownership of method, early. Frameworks you build will be applied to real companies and read by a very large retail audience.

Close work with a research desk that has been at this since 1990, and direct exposure to rating methodology built over three decades.

Real say. Analysts here argue with each other, and a quant who defers to seniority is not doing the job.

Engineering support, so your time goes on research rather than on data plumbing.

Competitive compensation, based on ability rather than years served.

Selection Process

Online Test

Assessment Round

Technical Round

HR Round (If Required)

Work Schedule Location

Work from Office: Monday to Friday (9:00 AM 6:00 PM)

Saturdays Sundays Off

Required Skills

SQL Data Handling

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

📌 Quant Analyst (Noida)
🏢 Value Research
📍 Noida