Data Quality Engineer
IMC Trading
Salary undisclosed
Need a reasonable accommodation to apply or interview? Contact us.
JobMinglr uses automated technology to recommend jobs based on profile information and job preferences. Match Score does not determine eligibility for a position, prevent a user from viewing or applying to a job, or make hiring decisions on behalf of an employer.
Description
At IMC, data shapes trading decisions across a wide range of financial products. The Data Quality team owns the integrity, completeness, and timeliness of the datasets our Quantitative Researchers and Traders rely on. As a Data Quality Engineer, you design the statistical methods that detect, characterise, and quantify issues in those datasets. Additionally, you own historical datasets that turn raw vendor and internal feeds into pricing-grade inputs and output.
Your responsibilities
Statistical methods
- Design statistical methods from first principles to detect outliers, distribution shifts, stale values, missing values, and inconsistencies across market datasets.
- Investigate anomalies, quantify their impact on pricing and trading decisions, and communicate findings through written analyses and design documents.
- Refactor and generalise methods as new asset classes and regions expose edge cases.
Historical Datasets
- 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.
Curation in production
- Roll out new and existing methods to production across regions and asset classes.
- Contribute production code in shared libraries
What you bring to the team
- 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.
About this role
IMC's Data Quality team sits at the foundation of the firm's trading operation—you'd be responsible for ensuring the datasets that drive quantitative research and trading decisions are accurate, complete, and timely. This role combines statistical method design with data engineering: you'll develop techniques to detect outliers, distribution shifts, and data inconsistencies across market datasets, then investigate what those anomalies mean for pricing and trading. You'll also own historical data pipelines, ingesting and cleaning feeds from external vendors and internal sources, and rolling statistical methods into production across regions and asset classes.
The position calls for someone with 3–5 years of experience working with large financial or scientific datasets and a Master's degree in a quantitative field like Mathematics, Statistics, Econometrics, or Physics. You'll need strong Python skills, particularly with statistical and time-series libraries, and comfort moving between exploratory analysis and production code. Beyond technical depth, the role requires direct communication with researchers and traders about data methodology and trade-offs—you're expected to be self-directed, intellectually curious about messy real-world market data, and genuinely interested in how financial markets work.
This is a full-time, in-office role based in Amsterdam. IMC is a research-driven trading firm that has operated since 1989, combining quantitative modeling, machine learning, and engineering to trade across global markets.
How this employer is doing
solid
- Hiring Mentioned
This role's local market on JobMinglr
Pay for this role
The employer didn't post a pay range for this role. That usually means pay is set in negotiation, which favors whoever arrives with numbers. Check ranges on comparable Data Quality Engineer postings in Amsterdam, and analyze any offer before you accept it.
Before you apply, worth reading
How JobMinglr reads this job
Every listing here is scored against your profile before you apply: skills overlap, experience level, location and work arrangement, each weighted and explained. You see the score and the reasons, not just a list. How the matching works.