Machine Learning Researcher

At Synthera AI, we are building proprietary machine learning models to simulate and forecast financial time series data, in particular publicly traded assets, starting with yield curves (and expanding to FX, commodities, equities and beyond).

With our synthetic data engine, investors and risk managers are able to test out thousands of highly realistic market scenarios, uncover complex correlations and more accurately capture tail risks, ultimately enhancing hedging strategies and improving risk-adjusted returns for asset managers, hedge funds, banks, insurers and other financial institutions.

We are backed by Entrepreneur First, Motive Partners, and KDX Ventures and other leading Venture Capital funds.

We also participated in the deep tech accelerator CDL and in Plug and Play’s Silicon Valley accelerator.

At Synthera we also have partnerships with UCL, Oxford, and Berkeley and are advised by a global leader in our field, Oxford Professor Rama Cont.

What you’ll be doing

We are looking for an ambitious, highly skilled Machine Learning Researcher to join our early team.

You’ll have the opportunity to make a direct impact on the company’s growth and trajectory from day one.

Key tasks include

• Designing, developing, and implementing deep learning models in alignment with the product roadmap, focused on time-series simulation for public capital markets.
• Identifying new methodologies to broaden the scope and capabilities of our machine learning models.
• Supporting in quantitative research and analysis, including the development of algorithms, and backtesting frameworks.
• Contributing to the overall development of the product, including tasks related to data pipelines, infrastructure, and optimisation of model performance.
• Refining methodologies, addressing technical challenges, and ensuring the performance of our machine learning models
• Ad-hoc support on related technical areas as reasonably required, within the scope of machine learning, quantitative finance, and product development.

Requirements

• Ph D in ML based time-series forecasting, simulation or analysis
• Experience in Deep Learning (or strong academic background in this field)
• Strong proficiency in on deep understanding of capital markets
• Experience in quantitative finance preferred but not required
• Ideally experience in developing and deploying deep learning models
• Expertise in DL frameworks and tooling (e. g., Py Torch, MLflow, etc.)
• Strong proficiency in Python

Why Join Us?

• Personal Growth and Upside Opportunities
• As an early team member, you’ll receive equity with significant growth potential as the company scales.

You’ll have a pivotal role with increasing responsibilities, including the opportunity to lead a team as we expand.

• Proprietary Cutting Edge Tech
• We are building proprietary generative AI models based on recent breakthroughs in ML for Quantitive Finance, pioneered by our scientific advisor.

Your role will be at the forefront of innovation and allow you to play a crucial role in the development of the product.

• Flexible Work
• Although we strongly believe in person collaboration, we also believe in flexiblity.

That is why we are offering employees the option (if desired) to work from abroad for a few months per year.

• Work with global leading experts
• Our Scientific Advisor, Professor Rama Cont from Oxford, is the global leading expert in this technology.

As an early member of the team you will have the opportunity to work directly with him.

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