Role at a glance
- Salary
- $192K – $260K/yr
- Location
- San Francisco, California, United States
- Work arrangement
- On-site
- Employment
- Full-time
- Experience
- 7+ years of data science, machine learning, and advanced analytics experience
- Education
- Masters or higher in quantitative fields or equivalent experience in industry
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Role Summary
The Trust and Safety Data Science team develops data-driven solutions that support the security, compliance, and governance of the Databricks Platform. This role partners with engineering, security, product, and trust and safety teams to detect fraud and abuse, protect customers from threats, and meet compliance requirements.
What You'll Do
- Develop and implement machine learning models to detect anomalous activity in Databricks products.
- Analyze the performance and pricing of security-related features and identify opportunities with product and engineering teams.
- Collaborate with security engineers, trust and safety experts, and machine learning engineers to build systems and tools that protect...
- Create solutions and frameworks to meet compliance requirements at Databricks.
- Gather requirements, define project OKRs and milestones, and communicate progress to technical and non-technical audiences.
- Guide junior data scientists and interns through project planning, technical decisions, and code and document review.
Generated from the employer's posting. Verify important details before applying.
View full postingQualifications
Understanding of good software engineering practices around testing, code reviews, and deployment; experience working in a highly cross functional alignment and talking about results to non-technical partners; experience deploying Data Science / ML solutions in production to achieve results; coding skills in SQL and a software development language (preferably Python); experience with distributed data processing systems like Spark and familiarity with software engineering principles.
Required
- 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 in a highly cross functional alignment and talking about results to non-technical partners
- Experience deploying Data Science / ML solutions in production to achieve results
- Coding skills in SQL and a software development language (preferably Python)
- Experience with distributed data processing systems like Spark and familiarity with software engineering principles
- Masters or higher in quantitative fields or equivalent experience in industry
Preferred
- Prior experience applying machine learning and data analytics to identify SaaS product misuse and enhance compliance preferred but not...
Original job description
Content provided by the employer
Original job description
Content provided by the employer
RDQ426R282
Databricks is building the world's best and most secure platform for data and AI. We innovate and deploy industry-leading solutions in security, compliance, and governance.
As a member of the Trust and Safety Data Science team, you will work on projects critical to ensuring the security and compliance of the Databricks Platform. Our customers depend on Databricks to keep their data safe, all while orchestrating millions of virtual machines across three clouds in dozens of regions around the globe.
Our engineering teams build highly technical products that fulfill real, important needs in the world. We always push the boundaries of data and AI technology, while simultaneously operating with the security and scale that is critical to making customers successful on our platform. We serve many companies with varying security and compliance needs. To efficiently serve these markets, we need to understand how customers use our existing features. This requires data-driven analysis of all aspects of security programs at Databricks.
Customers also trust Databricks with their most valuable data and we have the mission to build the most trusted data analytics and ML platform in the world. We’re looking to expand our Trust and Safety Data Science team. You will join a group of “full stack” data scientists who partner with engineering and security teams, focusing on strategic plans that make Databricks secure and safe for our customers. The team will use statistical and machine learning techniques for fraud and abuse detection on our platforms using state of the art methods . You can read more about some of our efforts in this blog post. The work in fraud and abuse detection is dynamic and essential, offering an opportunity to make a substantial impact in maintaining the security and efficiency of business operations.
More information is available at https://www.databricks.com/trust.
The impact you will have:
- You will develop and implement Machine Learning models to detect anomalous activity in products that we offer.
- You will analyze the performance and pricing of security-related features and work with product and engineering teams to identify important opportunities.
- You will collaborate with security engineers, trust and safety experts, and machine learning engineers to build a variety of systems and tools that protect Databricks and our customers from threats.
- You will create solutions and frameworks to meet compliance requirements at Databricks
- You will gather requirements, define project OKRs and milestones, and communicate progress to both technical and non-technical audiences.
- You will guide junior data scientists and interns on the team by helping with project planning, technical decisions, and code and document review.
- You will represent the data science discipline throughout the organization, using your powerful voice to make us more data-driven.
- You will represent Databricks at academic and industrial conferences and events.
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 in a highly cross functional alignment and talking about results to non-technical partners.
- Experience deploying Data Science / ML solutions in production to achieve results.
- Coding skills in SQL and a software development language (preferably Python)
- 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 but not required.
- Masters or higher in quantitative fields or equivalent experience in industry
Pay Range Transparency
Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected salary range for non-commissionable roles or on-target earnings for commissionable roles. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, Databricks anticipates utilizing the full width of the range. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above. For more information regarding which range your location is in visit our page here.
About Databricks
Databricks is the Data and AI company. More than 20,000 organizations worldwide — including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 — rely on the Databricks Data + AI Platform to build and scale data and AI apps, analytics and agents. Headquartered in San Francisco with 30+ offices around the globe, Databricks offers a unified platform that includes Genie, Lakebase, Agent Bricks, Lakeflow, Lakehouse, and Unity Catalog. To learn more, follow Databricks on LinkedIn, X, YouTube, and Instagram.
Benefits
At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click here.
Our Commitment to Diversity and Inclusion
At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics.
Compliance
If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.
About the company
Databricks
Large Enterprise
Databricks is a cloud-based data platform that specializes in providing solutions for data engineering, machine learning, and analytics. Founded in 2013 by the original creators of Apache Spark, the company enables organizations to unify data processing and analysis workflows, facilitating collaboration for data professionals. Databricks offers an integrated environment for data scientists, engineers, and business analysts, streamlining the process of building and deploying AI and data-driven applications. With a strong emphasis on simplifying big data management, Databricks helps businesses harness the power of their data to drive innovation and insights.
Databricks is a cloud-based data platform that specializes in providing solutions for data engineering, machine learning, and analytics. Founded in 2013 by the original creators of Apache Spark, the company enables organizations to unify data processing and analysis workflows, facilitating collaboration for data professionals. Databricks offers an integrated environment for data scientists, engineers, and business analysts, streamlining the process of building and deploying AI and data-driven applications. With a strong emphasis on simplifying big data management, Databricks helps businesses harness the power of their data to drive innovation and insights.