Quantitative Researcher at Seldon Capital

Important: This role is intended for college graduates with min. 1 year industry experience (non-internship roles) in quantitative research, trading, or applied machine learning. Undergraduates or Graduates without industry experience should apply to our Quantitative Research Internship role.

Seldon Capital is an investment firm based in San Francisco. Our mission is to push forward the craft of investing by combining deep fundamental research and machine learning. Our focus is on forecasting boom and bust cycles caused by new technologies, industry change, and government policy. We seek to understand and predict the future quality of businesses which sit at the fulcrum of value creation and destruction in those cycles.

We invest long and short across stocks, bonds, currencies, and commodities. The team previously worked together at Soros Fund Management and have worked separately at firms such as Lone Pine Capital, Goldman Sachs, Balyasny, and Coatue.

We are looking for a Data Science Engineer to lead our efforts in building a platform that structures and integrates financial datasets into our modelling systems. A large focus will be placed on joining, enriching, and transforming these datasets to create novel macroeconomic indicators. Our ideal candidate will also take a proactive approach to helping evolve our ML systems, while also looking for high value areas in the business that would benefit from automation.

The role at a broad level would be a hybrid one that combines both data science and systems engineering.

• Understanding how data is used at the firm both conceptually and from a technical construction perspective
• Building robust data ingestion pipelines and platforms
• Designing domain-specific features from data, relevant to industry and macroeconomic factors
• Automating and improving existing processes used throughout the firm, by developing tools and evolving systems
• Understanding the firm’s latest ML models & back testing systems, and assisting with their development

• Advanced degree in Computer Science
• 3+ years of experience in data analysis or similar role, preferably in industry setting
• Proficient in mathematical modelling, time series analysis, and machine learning techniques
• Advanced coding skills in Python, with track-record of writing maintainable code
• Experience with data storage tools such as SQL, Elasticsearch & Kibana, and Pandas
• Experience with ETL technologies, and interfacing with web API’s
• Experience with analyzing tabular data and implementing ML models such as Random Forest, XGBoost, etc
• Broad technical knowledge with respect to processing / exploration of data, data analytics pipelines, and interest in exploring new technologies
• Passion for automation and continual improvement, with track record of identifying high value automation opportunities
• Excellent software engineering skills with experience in building performant and maintainable architectures

Competitive compensation commensurate with experience, plus meaningful performance-based bonus.

Seldon Capital is an equal opportunity employer and is committed to creating a diverse and inclusive work environment. We encourage applications from all qualified candidates, regardless of race, color, religion, sex, national origin, age, disability, or any other protected status.