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Machine Learning Engineer - Strategic Data Solutions (Compliance)

Apple· Corporate Functions
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ShanghaiFull-timePosted 1w ago

About the role

SDS Machine Learning Engineer to design, build, and operate compliance analytics solutions that mitigate monetary losses, ensure regulatory compliance, and improve customer experience. Focus on real-time and batch production decisioning, leveraging Python, Scala, SQL, Spark, and related tools, with emphasis on privacy, regulatory changes, and scalable data science methods.

Responsibilities

  • Engage with business teams to identify opportunities, understand compliance requirements, and translate them into technical solutions.
  • Design a data science approach and develop algorithms for compliance problems when needed.
  • Collaborate with engineers and platform architects to implement robust production real-time and batch compliance decisioning solutions.
  • Ensure operational, regulatory, and business metric health by monitoring production decision points.
  • Investigate emerging risk typologies and regulatory changes; identify behaviors and respond with agile logic updates.
  • Communicate results of analyses to business partners and executives; partner with teams to find additional opportunities and services that improve loss avoidance and customer experience.

Qualifications

  • Education in a quantitative field (Computer Science, Applied Mathematics, Statistics) or equivalent professional experience.
  • Practical experience with algorithms for classification, regression, clustering, and anomaly detection.
  • Working knowledge of relational databases (SQL) and large-scale distributed systems (Hadoop and Spark).
  • Ability to implement analytical pipelines and applications in a general programming language (Python, Scala, Java, or Clojure).
  • Experience with financial crimes compliance (AML, KYC, sanctions screening, or transaction monitoring).
  • Experience with model explainability, documentation, and auditability in regulated environments.
  • Ability to comprehend and debug complex systems integrations spanning toolchains and teams.
  • Ability to extract meaningful business insights from data and tell the story behind patterns.
  • Excellent presentation skills to distill analyses into business-focused takeaways.
  • Creativity to engineer novel features and signals; willingness to push beyond current tools and approaches.
  • Experience with Splunk or similar log analytics tools.

Skills

Required:Algorithms for classification, regression, clustering, and anomaly detectionRelational databases and SQLLarge-scale distributed systems (Hadoop, Spark)Programming languages (Python, Scala, Java, or Clojure)Communication and storytelling with data
Nice to have:Financial crimes compliance (AML, KYC, sanctions, transaction monitoring)Model explainability, documentation, auditabilityFeature engineering and signal developmentSplunk or log analytics tools
Last updated Oct 16, 2026. Interested? Apply on the company site.

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