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Software Engineer

Netflix - 1d ago

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Senior Software Engineer

Reddit - 4d ago

Lead Data Scientist - Anti-Money Laundering (AML)

Requirements:

  • Experience implementing, training, testing, and evaluating performance of Machine Learning systems
  • Strong Python knowledge. A big plus for proven familiarity and experience with OOP principles
  • Experience with statistical analysis, and ability to produce well-designed experiments
  • A strong product mindset with the ability to work independently in a cross-functional and cross-team environment
  • Good communication skills and ability to get the point across to non-technical individuals
  • Strong problem-solving skills with the ability to help refine problem statements and figure out how to solve them

Nice to haves:

  • Familiarity with automating operational processes via technical solutions, for example Large Language Models
  • Willingness to get hands dirty with operational side by sides to understand their pain points
  • Knowledge and experience within the Financial Crime domain

What you'll be doing:

  • AML Risk Detection System Development
    • Developing efficient and effective AML detection controls using a mixture of unsupervised, semi-supervised, and supervised learning with GenAI
    • Creating frameworks to prove controls coverage at a regional level
    • Developing technologies to serve Wise's diverse international user base
  • Working in Cross-Functional Teams
    • Working across functions to own and solve AML related problems at a global scale
    • Mentoring more junior members of the team on technical and non-technical skillsets
  • Performance Testing and Optimization
    • Evaluating our AML systems against internal and external benchmarks
    • Developing decisioning layers to find optimal trade-offs between precision and recall
    • Providing data-driven insights on potential outcomes under various scenarios
  • Operational Process Development
    • Collaborating with operational teams to refine processes, ensuring effective feedback integration into our automation systems
    • Designing and managing projects that utilize excess operational capacity, such as manual data labeling for model improvement
    • Creating systems which provide in-depth insight to investigators on red flags and typologies present on profiles/transactions
  • Deployment and Implementation
    • Packaging algorithms into deployable libraries/objects and transitioning them from staging to production environments
    • Implementing and maintaining scheduled processes for data gathering and model retraining using automated pipelines
    • Maintaining production-grade Python services

Perks and benefits:

  • We're people without borders — without judgment or prejudice, too. We want to work with the best people, no matter their background.
  • If you're passionate about learning new things and keen to join our mission, you'll fit right in.
  • Qualifications aren't that important to us. If you've got great experience and you're great at articulating your thinking, we'd like to hear from you.
  • Diverse teams build better products, so we'd especially love to hear from you if you're from an under-represented demographic.
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