The board
- Where
- Chicago
- Posted
- Sep 18
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.
What you'd do
- Analyze new datasets to profile their content, identify collection and storage requirements for data engineering teams and proactively surface insights about the datasets for data strategists and front-office stakeholders
- Collect metrics and analyze datasets across different dimensions of data quality including completeness, validity, accuracy, timeliness, and consistency
- Curate data catalog entries to ensure our research data assets are accurately represented and easily discoverable
- Engage with global front office research teams to support datasets throughout their lifecycle, addressing content inquiries and managing communications with external data vendors
- Monitor and resolve production data issues while engaging key stakeholders across multiple teams and facilitating global support
- Assist the wider team by identifying opportunities to improve existing datasets and data management processes
- 1-2 years of relevant experience
- Strong foundational knowledge of financial instruments and market data symbology, with an interest in developing further expertise in these areas
- Proficiency with SQL and Python for exploratory data analysis (PySpark, pandas, numpy, Jupyter Notebooks)
- Ability to document and clearly explain complex data analysis findings