ABOUT US:

Sanjay Saraf Educational Institute has taught finance for over three decades. Founded by Sanjay Saraf Sir, who started teaching in 1994 and has since mentored more than 10 lakh students, SSEI prepares candidates for CFA, FRM, CA, and ACCA, and is an Approved Prep Provider for the CFA Institute, GARP, and ACCA. Founder led, bootstrapped, headquartered in Kolkata.

THE ROLE:

SSEI is building an internal quant trading simulation. It is a new vertical for us, and one of our most exciting projects. It builds on what we are strongest at (markets, derivatives, and risk) but it is genuinely new territory: systematic, data driven, and built in code. You would be spearheading the engineering behind it.

The role has two parts. The quant simulation is the headline. Alongside it, you will be SSEI's in house technology owner: our website and LMS are built by external vendors, and you will own that code.

WHAT YOU WILL WORK ON:

The quant trading simulation

- The simulation engine: how strategies receive data, place trades, get filled, and are marked to market.
- Large market datasets: sourcing, cleaning, storing, and querying years of intraday and end of day data.
- Time series modelling: returns, volatility, correlation, regime behaviour.
- Honest backtesting: out of sample testing, costs, slippage, and the risk metrics that show whether a strategy is real.
- Using AI tooling to move faster through research and development.

In house technology for SSEI

- Owning the code behind our vendor built website and LMS, and being the technical counterpart our vendors work with.
- Updates,



maintenance, fixes, and keeping things running.
- Building and shipping landing pages for campaigns and launches.

WHAT WE ARE LOOKING FOR:

- A robust coder. Python first, including pandas and NumPy. SQL. Git. Enough HTML, CSS, and JavaScript to work in a codebase someone else wrote and ship a landing page.
- Into quant investing. Systematic trading is something you follow and have tested ideas in, not just read about.
- Good with numbers, and analytical. Strong statistics and probability. Sceptical of a result until it survives scrutiny.
- Time series and large datasets. Hands on modelling experience, and comfort with data big enough that naive code falls over.
- AI fluency. Hands on with LLM APIs and AI coding tools.
- Projects to show. Quant, data, or code work you have actually built.

This is not a fundamentals or valuation role. Experience counts, and so does intent. If you are early in your career but have built serious things on your own, apply. If you have years in a quant, trading, data, or engineering role, apply.

WORK MODEL

Either based out of

- Kolkata: on site, six days a week.
- Mumbai: hybrid. Two days a week in office, the rest remote.
- Full time only.

HOW TO APPLY

Put links to at least two projects at the top of your CV, ideally one quant or data project and one thing you have built and shipped. For each, add three or four lines: the problem, what you built, and what it does now.

Applications without project links will not be shortlisted.

Compensation is as per industry standards.

📌 Finance Technology Analyst (Delhi)
🏢 Sanjay Saraf Educational Institute(SSEI
📍 Delhi