Senior Data Engineer, Anti Financial Crime (Senior Business Analysis Manager)

OKX is seeking a Senior Data Engineer to explore the data landscape and prototype features for machine learning and rules, translating typologies and investigator hypotheses into measurable candidate variables. You will validate data quality, collaborate with modelers and investigators, and maintain a living feature catalogue to support regulatory look-backs and ad-hoc research.

Overview

Department

Engineering

Job type

Full time

Compensation

Salary not specified

Location

Singapore, Southeast Asia

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What You’ll Be Doing

Explore the data landscape: profile on-chain, off-chain, fiat and KYC datasets to understand structures, gaps and lineage. Document findings for downstream engineering teams.

Prototype features for ML & rules: translate typologies and investigator hypotheses into measurable candidate variables (e.g., velocity, counterparty risk scores, graph metrics) using SQL/Python and big data.

Validate data quality & drift: run one-off QC checks, anomaly detection and basic stratified sampling to confirm a feature’s stability before production hand-off.

Collaborate with modelers & investigators: iterate quickly on feature definitions, and refine logic based on model performance and investigative feedback.

Maintain a living feature catalogue: version each prototype, capture business meaning, lineage and sample metrics so production data engineers can industrialize it.

Support regulatory look-backs & ad-hoc research: replay historical data, craft quick queries and surface insights that help Compliance and Compliance Product teams respond to audits or enforcement actions.

Stay current: monitor emerging AML data-science techniques (graph ML, LLM embeddings, anomaly detection) and assess their applicability to crypto and fiat monitoring.

What We Look For In You

4+ years in data engineering / analytics with hands-on feature-engineering and exploratory data analysis; AML or broader compliance experience is a plus.

Expertise in SQL and Python (Pandas, PySpark, or similar) within notebook workflows, plus hands-on experience with big data stacks such as Spark/Hadoop, Databricks and Alibaba DataWorks

Solid grounding in machine-learning fundamentals (supervised, unsupervised, evaluation metrics) and how features impact model performance.

Experience translating AML / regulatory concepts into quantitative features—e.g., structuring, layering, sanctions exposure.

Strong exploratory mindset: you’re comfortable with messy, ambiguous data and love turning it into structured insight.

Effective communicator who can collaborate with downstream data engineers and data scientists and explain feature logic to investigators and auditors.

Ability to work collaboratively in a fast-paced, dynamic environment.

Self-directed, curious, and hungry to experiment with new data sources — blockchain analytics, vendor feeds, public datasets.

Bonus: Working knowledge of the crypto ecosystem, VASP regulations, and typical AML data flows (KYT, KYC, TM, case management).

Perks & Benefits

Competitive total compensation package

L&D programs and Education subsidy for employees' growth and development

Various team building programs and company events

Wellness and meal allowances

Comprehensive healthcare schemes for employees and dependants

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