Job Summary

Dolat Capital is seeking a Quantitative Developer to build and optimise algorithmic trading strategies, work with real-time market data, implement low-latency systems, and collaborate with traders & researchers. Based in Mumbai, the role demands strong programming (Python/C++/Java) skills and a passion for financial markets. :contentReference[oaicite:1]{index=1}

Key Responsibilities

• Design, implement and optimise quantitative trading strategies for equities, futures, options and ETFs. :contentReference[oaicite:2]{index=2}
• Build trading systems and tools capable of high throughput, low latency, and real-time risk/PNL monitoring. :contentReference[oaicite:3]{index=3}
• Work closely with data scientists and traders; convert research signals into production code and deploy into live systems. :contentReference[oaicite:4]{index=4}
• Analyse large datasets (tick data, market flows) to identify patterns, optimise models and improve performance metrics. :contentReference[oaicite:5]{index=5}
• Maintain code quality, modularity and performance; contribute to system architecture and review.

Required Skills & Qualifications

• Bachelor’s or Master’s in Computer Science, Mathematics, Statistics, Physics, Financial Engineering or equivalent. :contentReference[oaicite:6]{index=6}
• Strong programming proficiency in Python; knowledge of C++/Java is a plus. :contentReference[oaicite:7]{index=7}
• Good understanding of data structures, algorithms and working in Unix/Linux environment. :contentReference[oaicite:8]{index=8}
• Interest or experience in financial markets, trading, derivatives, and/or quantitative analysis. :contentReference[oaicite:9]{index=9}
• Ability to work under pressure, learn fast and adapt in a dynamic trading/tech environment. :contentReference[oaicite:10]{index=10}

Estimated Salary Structure

Based on available market data for the role in Mumbai/India: :contentReference[oaicite:11]{index=11}

• Typical annual CTC: ~₹ 7,00,000 to ₹ 17,00,000 depending on experience and skills.
• For highly talented candidates (strong quant + programming + trading impact) compensation may be higher, including bonus/variable pay.
• Components often include base salary, performance bonus and benefits (insurance, training, PF etc.).

How to Prepare

1. Brush up programming & data structures: Work on Python/C++ problems, algorithms, data structures, and system performance.
2. Understand trading & financial markets: Study market micro-structure, derivatives (futures, options), order book dynamics, high frequency trading basics. :contentReference[oaicite:12]{index=12}
3. Practice with real-time/data-pipeline problems: Simulate tick-data ingestion, latency challenges, backtesting frameworks and optimisation loops.
4. Create a portfolio/GitHub: Showcase projects like strategy simulation, signal generation, backtesting, small trading systems and documentation of results/impact.
5. Prepare for interviews: Expect algorithmic/programming rounds, quant/math puzzles, market & trading questions, behavioural fit for high-performance environment. :contentReference[oaicite:13]{index=13}

Interview Tips & Probable Questions

• Explain a trading strategy you’d design: what data you’d use, how you’d simulate/backtest, how you’d deploy it.
• Write a function that given tick data returns the moving average of last N ticks efficiently — what data structure/algorithm would you use?
• Describe how you’d optimise latency or throughput of a trading system: e.g., Python vs C++ trade-off, memory usage, network I/O considerations.
• Discuss an extreme market event (flash crash, liquidity withdrawal) and how your system would survive, alert, or mitigate risk.

Company Overview

Dolat Capital Market Pvt. Ltd. is a multi-strategy investment management firm and financial advisory house in India. It emphasises analytic, systematic and disciplined approaches to trading and technology. :contentReference[oaicite:14]{index=14}

Pros & Cons (for Job Seekers)

Latest Trends & What Dolat Capital Is Doing

• Growing use of machine learning and quantitative methods in trading; companies like Dolat capital are increasingly combining statistics/data science with algorithmic trading. :contentReference[oaicite:18]{index=18}
• Focus on performance, latency optimisation, micro-structure analysis and high throughput systems for equities/futures. :contentReference[oaicite:19]{index=19}
• Quant roles increasingly expect full-stack capability: programming, quant modelling, trading knowledge, systems thinking.