Junior Quantitative Developer Jobs (NOW HIRING)

We are looking for a Junior Quantitative Developer to join our Quantitative Research & Development team, supporting our West Power Trading and Carbon desks. This role will be based in our New York City office with an expectation to work on-site 4-days per week. Reporting to the Lead Quantitative Developer in Stamford, CT, you will work closely with traders, analysts, and fellow quants to develop and maintain the quantitative tools, analytics, and models that support commercial decision-making across North American power and environmental markets. 

This is an excellent opportunity for an early-career quantitative developer who enjoys solving complex problems at the intersection of software engineering, mathematics, and commodity markets. You will gain exposure to one of the most dynamic areas of energy trading while contributing directly to trading strategies, pricing, risk management, and market analysis. 

This will be a full-time role, owning the following responsibilities: 

• Support the West Power and Carbon trading desks by working closely with quant researchers to productionize, optimize and support ML-based models relied upon by traders and analysts.  
• Enhance and maintain cloud-based infrastructure utilized by quant researchers and analysts to prototype and test new quant models. 
• Contribute to the automation of trading and operational processes to improve efficiency and reliability. 
• Monitor and troubleshoot production systems and respond to issues impacting trading activities. 
• Work closely with colleagues across New York, Stamford and Houston within a collaborative, fast-paced trading environment. 

You are a curious and analytical problem solver with a strong technical foundation and an interest in commodity markets. You enjoy working collaboratively, are eager to learn from experienced market participants, and thrive in an environment where technology has a direct commercial impact. 

The following education, experiences and skills are essential for application: 

• A bachelor's degree in a STEM subject, or a related quantitative field from a premier academic institution. 
• Two to four years of hands-on experience. 
• Strong practical skills with Python (e.g. pandas/numpy/plotly/Jupyter). 
• Solid understanding of algorithms, data structures, and software engineering best practices. 
• Proficient with object-oriented design and programming. 
• Knowledge of probability, statistics, linear algebra, and numerical methods. 
• Experience building analytics dashboards using frameworks like Dash. 
• Experience working with SQL and large datasets. 
• Strong analytical and problem-solving skills with excellent attention to detail. 
• Effective communication skills and the ability to work with both technical and commercial stakeholders. 
• A proactive mindset with a willingness to take ownership and continuously improve processes. 

In addition, the following experiences are not required, but highly desirable for this role:  

• A bachelor's, master's, or Ph.D. in Computer Science/Math/Statistics/Physics from a premier academic institution. 
• Comfortable with cloud platforms, preferably AWS, and experience with developing cloud-native microservices, stateless architecture, data object stores, containers, event-based triggers, queues, stream processing, etc. 
• Familiarity with time series analysis, forecasting techniques, or optimisation methods. 
• Experience building AI agentic workflows to retrieve/process data. 
• Exposure to energy, commodities, or financial markets. 
• Understanding of power markets, emissions markets, or energy systems. 

• An annual base salary of $150,000 to $180,000 USD and a discretionary annual bonus, based on performance.  
• 20 days of annual holiday entitlement, excluding US public holidays (NYSE). 
• Robust benefits package such as Medical, Dental, Vision, Life insurance, 401(k) match, and supplemental benefits partially subsidized by the Company.  
• Eligibility to receive external and internal training in accordance with our Training & Development Policy.