Data Quality Engineer

Ingest, assess, clean and maintain historical data from various external sources by designing and owning automated pipelines for corrections

Engage researchers and traders directly on data trust, methodology, and trade-offs.

Coordinate across curators, quantitative researchers, and developers for each dataset.

Roll out new and existing methods to production across regions and asset classes.

Contribute production code in shared libraries

3–5 years working with large-scale financial or scientific datasets.

A Master's degree in a quantitative discipline (Mathematics, Statistics, Econometrics, Physics, or similar).

Strong Python including the statistical libraries used for time-series analysis and surface fitting.

Comfortable moving between interactive analysis and production code.

A self-starter who finds the work that must be done, and does it without direction

Direct stakeholder communication with researchers and traders on data trust.

Intellectual curiosity about messy real-world market data.

Genuine interest in financial markets (no prior knowledge or experience is required)

About Us

IMC is a research-driven trading firm where quantitative modeling, machine learning, and engineering shape how modern markets are traded. A stabilizing force in markets since 1989, we provide liquidity across trading venues, delivering the best outcome in value and risk management to investors. Using our own technology and capital, we build proprietary systems and algorithms that operate across global markets. Our researchers, traders, and engineers work as a collective, combining rapid experimentation, advanced infrastructure, and real-time feedback to turn insight into execution and execution into advantage.