DRW is a diversified trading firm with over 3 decades of experience bringing sophisticated technology and exceptional people together to operate in markets around the world. We value autonomy and the ability to quickly pivot to capture opportunities, so we operate using our own capital and trading at our own risk.

Headquartered in Chicago with offices throughout the U.S., Canada, Europe, and Asia, we trade a variety of asset classes including Fixed Income, ETFs, Equities, FX, Commodities and Energy across all major global markets. We have also leveraged our expertise and technology to expand into three non-traditional strategies: real estate, venture capital and cryptoassets.

We operate with respect, curiosity and open minds. The people who thrive here share our belief that it’s not just what we do that matters–it's how we do it. DRW is a place of high expectations, integrity, innovation and a willingness to challenge consensus.

We’re looking for a curious problem‑solver who enjoys exploring ambiguous data and turning puzzles into answers. You’ll lead open‑ended investigations of HTTP traffic: cleaning and transforming logs, probing and visualizing patterns, formulating and testing hypotheses, and identifying root causes in the clients, the network, or servers. Deliverables include interactive visualizations and compact, well‑engineered Python scripts that speed up testing and troubleshooting.

How you will make an impact

• Lead open-ended investigations into HTTP request telemetry to find hidden patterns, anomalies, and regressions.
• Spin up reproducible analyses quickly (Python/Jupyter, pandas, numpy) and distill findings into concise notes teams can act on.
• Use CS fundamentals and networking knowledge (TCP/IP, HTTP semantics, TLS, CDN/proxy effects) to separate client, network, and server causes.
• Build small, robust CLIs/scripts to replay requests, synthesize test traffic, normalize logs, perform lightweight tests, or compute streaming metrics.
• Implement pragmatic data-processing approaches for large logs (chunking, Parquet, streaming).
• Deliver interactive visualizations and actionable recommendations that our developers can use for triage.

What you bring

• Bachelor’s or Master’s in Computer Science, Data Science, Engineering, Mathematics, or equivalent.
• Experience in exploratory data analysis using Python and pandas.
• Experience creating data visualizations (Matplotlib, Seaborn, Plotly, etc.); Plotly is a plus.
• Strong CS fundamentals: algorithmic thinking, data structures, and complexity-aware design.
• Practical networking knowledge: HTTP headers/status codes, TCP basics (retransmits, RTT implications), TLS concepts, and CDN/proxy behaviors and how they appear in telemetry.
• Strong communication skills: able to explain technical findings clearly to developers and operations, produce concise write-ups or notebooks, and collaborate effectively across teams.

Bonus points

• Experience with applied statistics and statistical modeling for time-series and anomaly detection (e.g., change-point detection, time-series decomposition, forecasting, or related methods).
• Familiarity with pcap/wireshark, distributed tracing, or lower-level network traces.
• Past experience in high-pressure investigation environments (operations, incident response).
• Background in quantitative roles (quantitative researcher/analyst or data scientist/analyst) or experience working with low-latency data streams is a plus.

What success looks like

• Consistent delivery of reproducible investigations that turn ambiguity into prioritized, actionable items.
• Dashboards or tools adopted by developers and operations that measurably reduce mean time to detect/triage incidents.
• Clear, concise reports that communicate findings and next steps.

For more information about DRW's processing activities and our use of job applicants' data, please view our Privacy Notice at https://drw.com/privacy-notice.

California residents, please review the California Privacy Notice for information about certain legal rights at https://drw.com/california-privacy-notice.

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