Job Description

This role is for one of our clients

Industry: Staffing and Recruiting
Seniority level: Associate level

Min Experience: 2 years
Location: Bangalore, India
JobType: full-time
We are looking for a Quantitative Trading Scientist to research, prototype, and validate systematic trading models driven by data, mathematics, and statistical rigor. This role blends deep quantitative thinking with hands-on programming, focusing on transforming market data into repeatable, testable trading logic.
You will work at the intersection of research and engineering--designing models, analyzing market behavior, and turning hypotheses into scalable code that can be evaluated across large financial datasets.

What You'll Do

Quantitative Research & Strategy Development

Research and develop systematic trading approaches using statistical and mathematical techniques.
Explore market microstructure and price dynamics to uncover predictive patterns.
Design robust signal-generation frameworks and evaluate risk-adjusted performance.

Data Analysis & Modeling

Analyze high-frequency and historical financial data, including tick data and order-book information.
Build and validate time-series and probabilistic models to capture market behavior.
Apply optimization techniques to improve strategy stability and execution efficiency.

Implementation & Experimentation

Translate research ideas into efficient, production-quality Python code.
Build reusable backtesting and research components to evaluate strategies at scale.
Perform rigorous testing, validation, and sensitivity analysis to reduce overfitting.

Collaboration & Deployment Support

Partner with engineering and trading teams to move models from research into live or simulated environments.
Assist in performance monitoring, model iteration, and post-deployment analysis.

Ideal Candidate Profile

Strong academic foundation in

Mathematics, Statistics, Physics, Operations Research, or Computer Science

.
2-4 years of experience in quantitative research, trading, or data-intensive modeling roles.
Deep understanding of probability, statistical inference, time-series analysis, and optimization.
Ability to reason from first principles and challenge assumptions using data.

Technical Expertise

Advanced Python for numerical and statistical computing.
Experience with libraries such as

NumPy, Pandas, SciPy, statsmodels, and scikit-learn

.
Practical knowledge of time-series methods (e.g., filtering, volatility modeling, regime detection).
Familiarity with version control systems and collaborative research workflows.

Nice to Have

Experience with strategies like statistical arbitrage, mean reversion, or momentum.
Exposure to models such as Kalman Filters, GARCH, or state-space methods.
Well-organized research repositories, notebooks, or backtesting frameworks demonstrating quantitative rigor.
Understanding of market microstructure or execution-related constraints.

Why This Role

Work on intellectually challenging problems at the intersection of math, data, and markets.
High ownership over research ideas and their real-world evaluation.
Opportunity to grow into advanced quantitative, trading, or research leadership roles.
Collaborative environment that values clarity of thought, experimentation, and disciplined execution.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.