Python Developer | Sports & Predictions | Experienced Hire

Susquehanna; Bala Cynwyd (PA); On-site; USD 140,000 - 240,000; Full time

Job summary

Susquehanna International Group, LLP is seeking a Front Office Python Engineer for trading applications in Bala Cynwyd, PA. You will build trader-facing Python tools for data analysis, visualization, and informed decision-making across trading and development desks.

You will work on backtesting, analytics, and real-time trading workflows, partnering with traders, quants, and technologists to turn data into actionable insights and scalable tooling.

Qualifications

• 3+ years of professional Python application or data system experience.
• Strong Python skills with Pandas, NumPy, and data processing libraries.
• Experience building data pipelines and working with APIs and real-time data feeds.
• Familiarity with data visualization tools and event-driven architectures.

Responsibilities

• Research, design, and develop systems used in backtesting and data analysis.
• Build Python-based applications and tools that deliver tactical analytics for trading decisions.
• Strategy monitoring and diagnostics.
• Develop ad-hoc tools and systematic data solutions.
• Improve trading workflows and optimize performance.
• Design and maintain data pipelines and datasets supporting research and trading.

Skills

Python programming

Data analysis

Backend development

Data pipelines

AI tooling

Real-time systems

Tools

Pandas

NumPy

Flask

FastAPI

SQL

Job description

Overview

Front Office Python Engineer - Trading Applications

We are hiring Python Engineers to build and evolve trader-facing applications that power data analysis, visualization, and decision-making across trading and development desk in our prediction markets team.

We specialize in geopolitical and sports analytics across the globe. This is an opportunity to build out a next gen sports trading system within an early-stage initiative focused on influential product development.

This role combines data engineering, application development, and quantitative tooling, with a focus on delivering systems used in backtesting, analytics, and real-time trading workflows. You will work closely with traders, quantitative analysts, and technologists to turn data into actionable insights and scalable tools.

What you'll work on:

• Research, design, and develop systems used in backtesting and data analysis
• Build Python-based applications and tools that deliver tactical analytics for trading decisions

• Strategy monitoring and diagnostics
• Develop both ad-hoc tools and systematic data solutions
• Improve trading workflows and optimize performance

• Design and maintain data pipelines and datasets supporting research and trading
• Continuously refine systems based on desk feedback and evolving trading strategies

What we're looking for

• 3+ years of professional experience building Python applications or data systems
• Strong Python skills, including experience with:
  • Pandas, NumPy, and data processing libraries
  • Backend frameworks (Flask, FastAPI, or similar)
• Experience working with:
  • Data pipelines and structured/unstructured datasets
  • APIs and real-time data feeds
  • SQL and database systems
  • AI tools to improve code quality, performance, and developer productivity
• Familiarity with:
  • Data visualization tools
  • Exposure to real-time systems or event-driven architecture

About Susquehanna

Susquehanna is a global quantitative trading firm powered by scientific rigor, curiosity, and innovation. Our culture is intellectually driven and highly collaborative, bringing together researchers, engineers, and traders to design and deploy impactful strategies in our systematic trading environment. To meet the unique challenges of global markets, Susquehanna applies machine learning and advanced quantitative research to vast datasets in order to uncover actionable insights and build effective strategies. By uniting deep market expertise with cutting-edge technology, we excel in solving complex problems and pushing boundaries together.