Quantitative Software Engineer (DV Commodities)

Posted 2 Days Ago
Be an Early Applicant
London, Greater London, England, GBR
In-Office
Junior
Financial Services
The Role
Build and productionize quantitative trading tools, energy-market models, analytics, data pipelines, and visualization tools. Collaborate with traders, quants, and engineers to develop signal research, backtesting, risk and pricing integrations, and time-series data infrastructure. Monitor, test, document, and iteratively improve production models and tools based on trader feedback.
Summary Generated by Built In

About Us:

DV Trading, LLC is a proprietary trading firm with over 200 employees trading equities, fixed income, FX and commodity products. DV Commodities is a rapidly growing division that specializes in trading crude oil, refined products, natural gas, and other commodities across US, European, and Asian markets. Our combined risk management, world class technology, and human capital have enabled us to become one of the largest liquidity providers within the global energy complex. 

Overview:

DV is looking for a software engineer with a quantitative mindset to join a small team building the tools that power our commodities trading. You will work directly with traders and quants to turn ideas into production-grade quant trading tools, fundamental analysis models, and analytics, and you will own them from prototype through daily use.

Job Responsibilities:

• Work alongside traders, quants and other engineers to build quant trading tools, including signal research, backtesting frameworks, and strategy monitoring

• Develop and productionize fundamental models for energy markets, such as supply/demand balances, inventory and flow analysis, and curve and spread models

• Build analytics and visualization tools that give traders clear, timely views of markets, positions, and PnL drivers

• Design data pipelines that ingest, clean and store market, fundamental, and alternative data from internal and third-party sources

• 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.

Skills Required

  • Bachelor's degree or higher in computer science, engineering, mathematics, statistics, physics, or another quantitative discipline
  • At least 2 years of professional experience building quantitative trading tools, models, or analytics in a financial or commodities setting
  • Strong Python skills in a scientific computing environment
  • Strong grounding in statistics, time series analysis, and data modeling
  • Experience building data pipelines and working with large datasets
  • Experience with SQL, NoSQL, or tick databases
  • Experience with data visualization and dashboarding tools
  • Strong knowledge of algorithms, design patterns, and object-oriented programming
  • Experience working in a Unix environment and Git
  • Strong verbal and written English communication skills
  • Machine learning experience
  • Java or C++ experience
  • Familiarity with Kafka, Docker, Airflow, or Luigi
  • Domain knowledge in energy markets, futures, and swaps
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The Company
HQ: Chicago, IL
314 Employees
Year Founded: 2006

What We Do

Founded more than 15 years ago and headquartered in Chicago, the DV Group of financial services firms has grown to more than 350+ people operating throughout North America and in Europe. Since spinning out of a large brokerage firm in 2016, DV Trading has rapidly scaled as an independent proprietary trading firm utilizing its own capital, trading strategies, and risk management methodologies to provide liquidity to worldwide financial markets and hedging opportunities to commodity producers and users. Now, DV group affiliates include two broker dealers, a cryptocurrency market making firm, and a bourgeoning investment adviser. We invest in exceptional individuals and empower them to realize their goals and make a lasting positive impact on our organization. Engaging a diverse group of talented people from different cultural, socioeconomic, and educational backgrounds helps provide us with a competitive advantage that drives our success.

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