Create efficient storage and access schemes for time series, reference, and fundamental data
Integrate models and tools with our event-based risk, market data and pricing platform
Test, monitor and document models and tools, and iterate quickly based on trader feedback
Requirements
Bachelor’s degree or higher in CS, Engineering, Mathematics, Statistics, Physics or another quantitative discipline
2+ years professional experience building quantitative trading tools, models, or analytics in a financial or commodities setting
Strong Python skills in a scientific computing environment (numpy, pandas, scipy, statsmodels or similar)
Solid grounding in statistics, time series analysis, and data modeling; machine learning experience is a plus
Experience building data pipelines and working with large data sets • Experience with SQL, NoSQL or tick databases
Experience with data visualization and dashboarding tools (e.g., Plotly/Dash, Streamlit, Grafana)
Strong knowledge of algorithms, design patterns, and OOP; Java or C++ is a plus
Experience working in a Unix environment and git
Familiarity with Kafka, Docker, Airflow, or Luigi
Strong communication skills in verbal and written English, with the ability to work closely with traders
Domain knowledge in energy markets, futures and swaps is a plus
Benefits
Discretionary bonus eligibility
Medical, dental, and vision insurance
HSA, FSA, and Dependent Care Options
Employer Paid Group Term Life and AD&D insurance
Voluntary LTD, Life & AD&D insurance
Flexible Vacation policy
Retirement plan with employer match
DV is not accepting unsolicited resumes from search firms. Only search firms with valid, written agreements with DV should submit resumes in response to DV’s posted positions. All resumes submitted by search firms to DV via e-mail, the Internet, personal delivery, facsimile, or any other method without a valid written agreement shall be deemed the sole property of DV, and no fee will be paid in the event the candidate is hired by DV. DV is proud to be an equal opportunity employer and committed to creating an inclusive environment for all employees.
