Quantitative Researcher - Experienced (DV Equities) at DV Trading LLC

<p data-renderer-start-pos="1" data-local-id="5d6d5c6caa36"><span style="font-size: 12pt;"><strong data-renderer-mark="true">About Us</strong>:</span></p> <p data-renderer-start-pos="1" data-local-id="5d6d5c6caa36"><span style="font-size: 12pt;">Founded two decades ago and headquartered in Chicago, the DV Group of financial services firms has grown to more than 600 people across North America, Europe and Asia. Since becoming an independent proprietary trading firm in 2016, DV Trading has scaled rapidly using its own capital, strategies and risk management to provide liquidity to markets worldwide. DV Group affiliates today include two broker-dealers, a cryptocurrency market maker and a growing investment adviser.<br>DV Equities is the group's Asia-Pacific equities and futures market-making business, trading cash equities, ETFs, index futures and related products on exchanges across the region.</span></p> <p data-renderer-start-pos="641" data-local-id="3db7b8c101de"><span style="font-size: 12pt;"><strong>Overview:</strong></span></p> <p data-renderer-start-pos="641" data-local-id="3db7b8c101de"><span style="font-size: 12pt;">We are looking for an experienced Quantitative Researcher to join our equities team. This role is open to candidates <span class="">with hands-on experience in multi-frequency signal research across different time horizons.</span>&nbsp;You will work closely with senior researchers and traders across our global offices (NYC, London, and Hong Kong) to explore market data, develop predictive signals, and build models that directly inform real trading decisions.</span><br><span style="font-size: 12pt;">This is a full-cycle research role—from data exploration to production deployment, from model development to live performance monitoring—with end-to-end ownership of the research process.</span></p> <p data-renderer-start-pos="731" data-local-id="db73e6d3f6c4"><strong><span style="font-size: 12pt;">Responsibilities:</span></strong></p> <ul> <li style="font-size: 12pt;"><span style="font-size: 12pt;">Analyze market data to uncover patterns, inefficiencies, and predictive signals across different time horizons</span></li> <li style="font-size: 12pt;"><span style="font-size: 12pt;">Build and backtest quantitative models using historical market data</span></li> <li style="font-size: 12pt;"><span style="font-size: 12pt;">Apply statistical and machine learning techniques—with an emphasis on tree-based methods—to enhance signal quality</span></li> <li style="font-size: 12pt;"><span style="font-size: 12pt;">Collaborate with researchers and traders to translate research insights into production-ready strategies</span></li> <li style="font-size: 12pt;"><span style="font-size: 12pt;">Develop and maintain data pipelines for large-scale, high-frequency, and time-series market data</span></li> <li style="font-size: 12pt;"><span style="font-size: 12pt;">Continuously monitor and iterate on live signals and models based on performance</span></li> </ul> <p data-renderer-start-pos="731" data-local-id="db73e6d3f6c4"><strong><span style="font-size: 12pt;">Requirements:</span></strong></p> <ul> <li style="font-size: 12pt;"><span style="font-size: 12pt;">2+ years of professional or research experience in high-frequency research and/or longer-term signal generation</span></li> <li style="font-size: 12pt;"><span style="font-size: 12pt;">Degree in a quantitative field (Mathematics, Statistics, Computer Science, Physics, Engineering, Financial Engineering, or related)</span></li> <li style="font-size: 12pt;"><span style="font-size: 12pt;">Strong proficiency in Python, including standard data science libraries (pandas, NumPy, etc.)</span></li> <li style="font-size: 12pt;"><span style="font-size: 12pt;">Genuine curiosity about financial markets and market microstructure</span></li> <li style="font-size: 12pt;"><span style="font-size: 12pt;">Solid foundation in statistics and quantitative analysis</span></li> <li style="font-size: 12pt;"><span style="font-size: 12pt;">Strong problem-solving skills and intellectual curiosity</span></li> <li style="font-size: 12pt;"><span style="font-size: 12pt;">Ability to communicate technical findings clearly to both technical and non-technical audiences</span></li> <li style="font-size: 12pt;"><span style="font-size: 12pt;">Familiarity with tree-based methods (e.g., Random Forest, XGBoost, LightGBM) is a plus</span></li> <li style="font-size: 12pt;"><span style="font-size: 12pt;">Experience in a proprietary trading or hedge fund environment is a plus</span></li> <li style="font-size: 12pt;"><span style="font-size: 12pt;">Experience with C++ or other low-level languages is a plus</span></li> </ul> <p data-renderer-start-pos="731" data-local-id="db73e6d3f6c4">&nbsp;</p> <p><em data-renderer-mark="true"><span data-highlighted="true" data-vc="highlighted-text">DV</span> is not accepting unsolicited resumes from search firms. Only search firms with valid, written agreements with <span data-highlighted="true" data-vc="highlighted-text">DV</span> should submit resumes in response to <span data-highlighted="true" data-vc="highlighted-text">DV</span>’s posted positions. All resumes submitted by search firms to <span data-highlighted="true" data-vc="highlighted-text">DV</span> via e-mail, the Internet, personal delivery, facsimile, or any other method without a valid written agreement shall be deemed the sole property of <span data-highlighted="true" data-vc="highlighted-text">DV</span>, and no fee will be paid in the event the candidate is hired by <span data-highlighted="true" data-vc="highlighted-text">DV</span>. <span data-highlighted="true" data-vc="highlighted-text">DV</span> is proud to be an equal opportunity employer and committed to creating an inclusive environment for all employees.</em></p>