Software Engineer, Data (Quantitative Investment Sciences)

Tiger Recruitment; New York (NY); On-site; USD 100,000 - 130,000; Full time

Job summary

Tiger Recruitment is partnering with a leading Hedge fund to find a Software Engineer, Data. This role is key to developing scalable data infrastructure and innovative tools that support quantitative research and trading strategies.

The ideal candidate will have at least 2 years of experience, strong Python and SQL skills, and a passion for problem-solving. Join this elite team and contribute directly to investment performance!

Qualifications

• Minimum 2 years' experience in software engineering.
• Strong proficiency in Python and SQL.
• Excellent written and verbal communication skills.
• Proactive, self-motivated, and comfortable taking ownership.

Responsibilities

• Design and maintain scalable software systems for data processing.
• Build software libraries that enhance research capabilities.
• Collaborate with researchers to support new investment strategies.

Skills

Python

SQL

Software engineering best practices

Problem-solving

Tools

CI/CD pipelines

Containerization

Spark

Airflow

Job description

Tiger Recruitment is partnering with a highly successful Tier 1 multi - strategy Hedge fundseeking a talented Software Engineer, Data to join its world-class Quantitative Investment Sciences team. This is an exceptional opportunity to work at the intersection of technology, data, and quantitative investing within a collaborative, intellectually rigorous environment. The successful candidate will join a revenue-generating team where their work will have a direct impact on investment performance and the development of cutting-edge research capabilities. Our client takes a scientific approach to understanding financial markets and is committed to building a culture where curiosity, innovation, and excellence drive results. The Opportunity Data is at the core of our client's investment edge. As a Software Engineer, Data, you will be responsible for designing and building scalable data infrastructure, developing innovative research tools, and enabling quantitative researchers to generate insights that power trading strategies. Working closely with researchers, engineers, and investment professionals, you will help create robust systems that support the full research and trading lifecycle, from data acquisition through to live deployment.

Key Responsibilities

• Design, develop, and maintain scalable software systems for large-scale data processing and analysis.
• Build innovative software libraries and enriched datasets that enhance research capabilities, including applications leveraging large language models (LLMs).
• Develop production-grade systems that transition research initiatives into live trading environments.
• Implement automated testing, monitoring, and validation frameworks to ensure the highest standards of data quality and reliability.
• Create and maintain APIs and data services that seamlessly connect research and trading platforms.
• Develop reusable software frameworks and components that accelerate quantitative research and engineering workflows.
• Collaborate closely with quantitative researchers to support the development and deployment of new investment strategies.

Candidate Profile Essential Requirements

• Minimum 2 years' experience in software engineering, ideally within fast-paced and data-intensive environments.
• Strong proficiency in Python and SQL.
• Excellent written and verbal communication skills.
• Solid understanding of software engineering best practices, including clean code principles, testing, and maintainable system design.
• Naturally curious with a passion for problem-solving and continuous learning.
• Proactive, self-motivated, and comfortable taking ownership of projects from concept through to delivery.

Desirable Experience

• Experience with distributed systems, microservices, or event-driven architectures.
• Exposure to DevOps methodologies and infrastructure automation, including CI/CD pipelines, containerisation, and monitoring tools.
• Knowledge of distributed computing frameworks such as Spark or Dask, and workflow orchestration platforms including Airflow, Dagster, or Prefect.
• Understanding of quantitative trading, financial markets, time-series data, or alternative datasets.
• Experience working with machine learning, natural language processing, or large language model applications.

What's on Offer

This is a rare opportunity to join an elite investment team where technology and research are central to competitive advantage. The successful candidate will work alongside some of the industry's brightest minds, contribute directly to investment outcomes, and help build the next generation of data-driven research and trading infrastructure.

Job ref NM 187771