Develops ML models for fraud/abuse detection and anomalous activity on Databricks platform. Analyzes security features, collaborates cross-functionally, and deploys production solutions. Requires 7+ years experience, MS in quantitative field, Python/SQL/Spark expertise.
192k – 260k
On-site7+ YOEData Science
About the role
Impact You Will Have
Develop and implement Machine Learning models to detect anomalous activity in products.
Analyze the performance and pricing of security-related features and work with product and engineering teams to identify opportunities.
Collaborate with security engineers, trust and safety experts, and machine learning engineers to build systems and tools that protect Databricks and customers from threats.
Create solutions and frameworks to meet compliance requirements.
Gather requirements, define project OKRs and milestones, and communicate progress to technical and non-technical audiences.
Guide junior data scientists and interns on project planning, technical decisions, and code review.
Represent the data science discipline organization-wide to drive data-driven decisions.
Represent Databricks at academic and industrial conferences.
What We Look For
7+ years of data science, machine learning, and advanced analytics experience in high-velocity, high-growth companies.
Understanding of good software engineering practices around testing, code reviews, and deployment.
Experience working cross-functionally and communicating results to non-technical partners.
Experience deploying Data Science / ML solutions in production.
Coding skills in SQL and a software development language (Python preferred).
Experience with distributed data processing systems like Spark and familiarity with software engineering principles.
Prior experience applying machine learning and data analytics to identify SaaS product misuse and enhance compliance (preferred).
Masters or higher in quantitative fields or equivalent industry experience.
Skills
Machine LearningPythonSQLSparkData ScienceSoftware EngineeringFraud DetectionAnomaly DetectionDistributed SystemsProduction Ml
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192k – 260k
On-site7+ YOEData Science
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