Tracxn - Quantitative Research Analyst

About the role:

We are hiring a Quantitative Research Analyst to estimate revenue for private companies that disclose little or nothing. You will combine benchmarks, financial models and statistical methods to turn sparse signals into revenue ranges and other relevant KPIs.

Location: Bengaluru

Reports to: Senior Vice President

Experience: 2 - 5 years

Team: Works with research analysts, data engineers and product

What you will do:

Estimation and modelling:

• Build top-down (market size x share) and bottom-up (customers x ARPU, headcount x revenue per employee, transactions x take rate) revenue models for private companies.
• Triangulate at least two independent methods per estimate and reconcile differences.
• Produce revenue ranges with stated confidence levels.

Benchmarking:

• Build and maintain peer sets and sector benchmarks from listed comparables and disclosed private-company financials.
• Normalise benchmarks for geography, stage, business model and currency.
• Maintain sector-specific heuristics for SaaS, marketplaces, D2C, fintech, B2B services and manufacturing.

Statistical methods and data:

• Develop regression and ML models that estimate revenue from proxies such as headcount, web and app traffic, hiring velocity, funding history and pricing.
• Source and evaluate alternative data, including regulatory filings (e.g. MCA/ROC), and quantify how reliable each signal is.
• Handle skewed distributions, missing data and outliers appropriately.

Validation and quality:

• Back-test estimates against actual financials as companies file or list, and track error rates by sector and size band.
• Document methodology and assumptions so any estimate can be audited and explained.
• Defend estimates in conversations with clients, sales and internal reviewers.

What you need:

• Bachelor's or Master's degree in Mathematics, economics, statistics, engineering or a related quantitative field.
• Strong financial modelling in Excel, including unit-economics and driver-based models.
• Working knowledge of statistics: linear and log-linear regression, distributions, confidence intervals and error measurement.
• Proficiency in SQL and Python or R for data handling and model building.
• Fluency with sector KPIs such as ARR, GMV, take rate, churn, CAC and revenue per employee.
• Sound commercial judgment: you sanity-check a number before you declare it.
• Clear written communication of methods, assumptions and uncertainty.

Nice to have:

• CFA (any level), FRM or a postgraduate degree in economics or statistics.
• Experience estimating financials for unlisted companies, e.g. at a rating agency, PE/VC firm or data provider.
• Exposure to alternative data: web traffic, app intelligence, job postings, trade or tax data.
• Familiarity with Bayesian or shrinkage methods, or gradient-boosted models, for estimation at scale.
• Deep knowledge of one or more sectors such as SaaS, fintech, consumer internet or B2B services.
• Experience with Indian regulatory filings (MCA/ROC) or equivalent registries in other markets.

What we offer:

• A role with significant responsibility and opportunity to create mathematical models for a range of businesses.
• Direct impact on a core data product used by investors and corporates.
• A meritocracy driven culture with respect for work-life balance.

Hiring process:

• 1. Introductory call (30 minutes)
• 2. Technical interview on modelling and statistics (45 minutes)
• 3. Case exercise: estimate an unlisted company's revenue from public signals, then present your range, method and confidence (90 minutes)
• 4. Final conversation with the hiring manager and team lead