Applied Scientist (Quantitative Trading)
New York, NY

Job Description

Are you passionate about leveraging geospatial data to help solve some of the world's most pressing and challenging scientific questions? Here at Descartes Labs, we house and process all publicly available satellite imagery, allowing scientists to focus solely on applying these data to answer real-world problems.

Descartes Labs is looking for an Applied Scientist with a focus on Machine Learning and Financial Trading.

Responsibilities

* Assimilate multiple data sets (public and proprietary, geospatial and transactional) to build market price models over various time horizons
* Model and simulate various forward-looking scenarios that take into account weather, geographic, political, economic, financial and other risks to assess impact on markets
* Leverage a wide array of technical tools to derive signal: machine learning, signal processing, statistics, financial modeling, risk modeling, and geospatial operations
* Synthesize the above to develop actionable, quantitative, backtested trading insights where all factors influencing a recommendation are fully understood
* Design and manage the production environments and processes that enable these products
* Determine repeated, automatable components and work with the product team to design and implement innovative and marketable tools that facilitate and scale this work

Requirements

* Advanced degree (MS/PhD) in a relevant field (finance, computer science, mathematics, statistics, etc.)
* Strong experience with machine learning
* Experience in developing financial/trading models that have had capital deployed against them
* Experience with stochastic (Monte Carlo) models
* Demonstrated proficiency in a scientific programming language (preferably Python)
* Strong written and verbal communication skills
* Ability to work independently; flexible and able to quickly adapt; self-motivated
* Proven ability to work and communicate efficiently with clients as well as organizational prowess for collaborative efforts with internal and external stakeholders

Pluses

* Experience with numpy, sklearn, scikit-image, matplotlib
* Experience with version control software (e.g. GitHub, Mercurial, etc.)
* Experience with cloud and/or distributed computing
* Time series analysis / signal processing
* Ability to coordinate complex technical production pipelines