Quantitative researcher Python - Trading systems

Company Description

Zoft.ai is an AI-powered SaaS platform designed to transform customer service by leveraging intelligent chat and voice agents. These advanced agents seamlessly provide personalized support while managing complex workflows and actions. The company's technologies ensure efficient and streamlined customer interactions that enhance user experience. Zoft.ai is dedicated to revolutionizing traditional service models through innovative AI solutions.

Role Description

This is a full-time remote role for a Quantitative Researcher specializing in Python and Trading Systems. The individual in this role will conduct quantitative research, analyze financial data, and develop trading strategies using Python. Responsibilities include statistical modeling, data analysis, and collaboration with the trading and engineering teams to optimize algorithms and system performance. The researcher will also be expected to stay updated on trends in financial markets and quantitative methodologies.

Qualifications

• Strong foundation in Statistics and Mathematics, with the ability to build robust quantitative models
• Proven expertise in Quantitative Research and Quantitative Investing
• Exceptional Analytical Skills with the ability to interpret complex financial data
• Have

  exceptional mathematical ability

  , with

  90%+ in 10th and 12th standard

• Come from a strong

  Mathematics / Statistics / CSE background

• Have completed formal learning or certification in

  Data Science, Machine Learning, or AI

• Proficiency in Python and its applications in algorithmic trading and data analysis
• Hands-on experience with trading systems and financial market analysis is highly desirable
• A master's or Ph.D. in a quantitative discipline such as Financial Engineering, Mathematics, or Computer Science is a plus
• Strong problem-solving and critical-thinking abilities
• Excellent communication skills and the ability to work effectively in collaborative, remote environments

• Design, build, and own

  Python-based quantitative backend systems

  for

  real-time market and trading data

• Work on

  low-latency system design

  supporting

  algorithmic trading and investment strategies

• Process and manage

  high-frequency financial time-series data

• Optimize

  InfluxDB and other data stores

  for

  large-scale trading and market data

• Build

  API-driven trading architectures

  used in live investment workflows
• Integrate with

  brokers, exchanges, and third-party market data providers

  using

  WebSocket and REST APIs

• Collaborate closely with

  quantitative researchers and investment teams

  to translate mathematical models into production trading systems

• Work From Office (WFO) – Mandatory

• Full-time, in-office role in Chennai

• Wall Street / Hedge Fund–style professional trading environment

• Work on

  live, production-grade investment and trading systems

• No remote or hybrid options

Location: