Senior Quant Developer

Sigma Software

12h•Remote

About The Position

Are you passionate about building quantitative trading systems that combine advanced analytics, machine learning, and high-performance engineering? We are looking for a Senior Quant Developer to join a cutting-edge financial technology project focused on algorithmic trading and portfolio optimization. In this role, you will work remotely with international teams across Ukraine and Europe, contributing to scalable research and investment platforms used in data-driven financial environments. You will have an opportunity to work with modern quantitative technologies, large-scale market data, and production-grade engineering practices. We at Sigma Software offer the flexibility of remote collaboration, professional growth opportunities, and the chance to work on impactful fintech solutions together with experienced engineering and quantitative teams. CUSTOMER Our Customer is a fast-growing technology company developing AI-driven solutions for the financial services industry. The company specializes in quantitative research, algorithmic trading, portfolio optimization, and intelligent investment platforms. By combining cloud-native engineering, machine learning, and quantitative analytics, the Customer delivers scalable and high-performance financial solutions for modern trading environments. PROJECT The project focuses on the development and enhancement of quantitative trading and portfolio management platforms. The team builds scalable systems for market data processing, strategy research, backtesting, portfolio optimization, and performance analysis across multiple asset classes. The solution integrates advanced analytics and machine learning into production-grade investment workflows while emphasizing automation, reliability, and engineering excellence in systematic trading environments.

Requirements

5+ years of commercial software development experience
Strong Python development expertise
Hands-on experience with Pandas, Polars, NumPy, or similar data processing libraries
Experience building quantitative analytics, research, or trading systems
Strong knowledge of statistics, probability, and quantitative modeling techniques
Experience with backtesting frameworks and performance analysis
Understanding of portfolio construction and risk management concepts
Experience working with relational and time-series databases
Practical knowledge of PostgreSQL or equivalent databases
Experience with Git, Docker, and CI/CD practices
Strong analytical thinking and problem-solving skills
Upper-Intermediate or higher English level

Nice To Haves

Experience with VectorBT, Backtrader, QuantConnect LEAN, or similar platforms
Exposure to machine learning frameworks such as PyTorch, XGBoost, or LightGBM
Knowledge of equities, futures, forex, or cryptocurrency markets
Experience with FIX protocol integrations
Exposure to Java or C++
Experience with cloud platforms and distributed systems
Background in institutional trading, fintech, or investment management solutions

Responsibilities

Design, develop, test, and deploy quantitative trading and portfolio management solutions
Develop and maintain research, backtesting, and portfolio optimization frameworks
Analyze historical and real-time market data across multiple asset classes
Implement validation, simulation, and performance testing methodologies
Integrate machine learning models into quantitative workflows where applicable
Collaborate with engineering and quantitative teams to deliver production-grade solutions
Contribute to software architecture, code quality, automation, and operational excellence
Monitor and improve strategy performance, scalability, and system reliability
Participate in technical discussions, design reviews, and solution planning
Optimize data processing pipelines and analytical workflows for performance and scalability