Quantitative Researcher

at  Sparta Commodities

Hey, we’re Sparta Commodities!
We are a Swiss, VC-backed scaleup with a global reach. Our mission is to digitize the commodity trading market and become the leading platform for traders in all commodities verticals. We’ve already gained significant market traction and are financially backed by Venture Investors.
Sparta currently has a fantastic opportunity for a driven and passionate Quantitative Researcher with a strong analytical mindset, and proven experience (2+ years) in time series forecasting, specifically in financial data, including the integration of alternative data sources.
We are a fully remote company with a modern tech stack, and we strive for fast deployments to support the rapid growth we are experiencing, these hires are key to our continued success.

QUALIFICATIONS:

• Ph.D./M.Sc. in a quantitative field such as Computer Science, Statistics, Mathematics, Physics, or a related discipline.
• Proven experience (2+ years) in time series forecasting, preferably within financial markets.
• In-depth knowledge of a broad range of statistical modeling methods and algorithms.
• Strong Python programming skills for data analysis and machine learning.
• Familiarity with software engineering best practices, including version control (e.g., git), code reviews, and collaborative development.

Bonus points:

• Experience in the commodities industry (e.g., oil & gas, electricity, etc.)
• Experience with Generative AI and/or Causal AI

What’s the culture like at Sparta?
At Sparta, our culture is not just a set of values written on a wall—it’s a way of life. We embrace a dynamic environment where initiative is celebrated, challenges are met head-on, and innovation thrives.
We’re building an environment where our employees thrive and excel in their work. Our aim is for every member of our team to take pride in their contributions. You’ll collaborate with like-minded individuals who are passionate about our mission and deeply committed to crafting outstanding products and achieving success for our customers.
We operate remotely, understanding that a thriving, profitable company isn’t just about being in the same location. We build our relationships through effective remote work methods and carefully planned in-person meet-ups.

• Develop advanced models for time series forecasting of financial data, ensuring accuracy and robustness.
• Analyze historical data trends, patterns, and alternative data sources to improve forecasting models.
• Continuously optimize models to adapt to changing market conditions and improve accuracy.
• Stay up to date on the latest developments in AI and explore its potential applications in our domain.
• Work closely with data engineers, quant developers, and domain experts to understand business requirements and translate them into actionable data science tasks.
• Collaborate with other members of the Data Team to share insights, techniques, and best practices.