Engage with business teams to find opportunities, understand compliance requirements, and translate those requirements into technical solutions.
Design a data science approach, applying tried-and-true techniques or developing custom algorithms as needed for the compliance problem.
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 behavior patterns, and respond with agile logic updates.
Communicate results of analyses to business partners and executives, and partner with teams across Apple to find additional opportunities and services that improve loss avoidance and the overall customer experience.
Minimum Qualifications
Education in a quantitative field, such as Computer Science, Applied Mathematics, or Statistics, or equivalent professional experience.
Practical experience with and theoretical understanding of algorithms for classification, regression, clustering, and anomaly detection.
Working knowledge of relational databases, including SQL, and large-scale distributed systems such as Hadoop and Spark.
Ability to implement analytical pipelines and applications in a general programming language such as Python, Scala, Java, or Clojure.
Preferred Qualifications
Experience with financial crimes compliance, such as 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 identify the stories behind the patterns.
Excellent presentation skills, distilling complex analysis and concepts into concise business-focused takeaways.
Creativity to engineer novel features and signals, and to push beyond current tools and approaches.
Experience with Splunk or similar log analytics tools.