Quantitative Software Engineer — Scalable ML for Markets

Edgestream; Princeton (KY); On-site; USD 120,000 - 180,000; Full time

Benefits offered by this job

Competitive pay

Bonus program

Data resources

Catered lunch

Onsite gym

Growth opportunities

Job summary

Edgestream’s Research group seeks a Software Engineer to help build quantitative software platforms for scientific exploration. You will maintain and extend ML tools and infrastructure, enabling researchers to run large-scale experiments with market data and alternative datasets.

The role emphasizes writing elegant, robust code and delivering scalable systems in a collaborative setting across Princeton, NJ or New York, NY. A strong background in Python, ML, and numerical libraries is essential.

Qualifications

• A Bachelor’s or Master’s degree in Computer Science, Engineering, or a closely related field.
• Strong Python programming and software design capabilities.
• Solid grounding in probability, statistics, and machine learning.
• Experience with NumPy/Pandas, scikit-learn or equivalent libraries.
• Ability to communicate effectively within a technical, collaborative team.
• Curiosity and passion for using tech to solve hard problems.

Responsibilities

• Maintain and build machine learning tools and research infrastructure.
• Support researchers running large-scale experiments with market data.
• Develop elegant code and robust, scalable software systems.
• Collaborate with researchers and engineers to tackle hard scientific problems.

Skills

Python programming

Software design

Machine learning

Numerical libraries

Communication

Education

Bachelor's or Master's in CS/Engineering

Tools

NumPy

Pandas

scikit-learn

Job description

Edgestream’s Research group seeks a Software Engineer to help build quantitative software platforms for scientific exploration. You will maintain and extend ML tools and infrastructure, enabling researchers to run large-scale experiments with market data and alternative datasets.

The role emphasizes writing elegant, robust code and delivering scalable systems in a collaborative setting across Princeton, NJ or New York, NY. A strong background in Python, ML, and numerical libraries is essential.