Top Tech Jobs & Startup Jobs in San Francisco Bay Area, CA

One Month AgoSaved
Remote
US
150K-200K Annually
Senior level
150K-200K Annually
Senior level
eCommerce • Insurance • Software
Lead company-wide People programs, advise executives on org design and succession planning, optimize HR processes with data and automation, drive performance management, compensation, leadership development, manager enablement, and employee engagement while mentoring the People team and ensuring compliance.
Top Skills: AIAutomationHrisLinkedin LearningMento
One Month AgoSaved
Remote
U.S.
160K-180K Annually
Senior level
160K-180K Annually
Senior level
eCommerce • Insurance • Software
Lead and build the Risk Analytics function: define pricing methodology and risk frameworks, own portfolio and pricing strategy, convert monitoring into decision systems, architect the Risk Analytics data layer (dbt/Snowflake), mentor senior data scientists, and represent risk recommendations to senior leadership to drive business decisions.
Top Skills: ClaudeDbtGeminiPythonRSnowflakeSQLStreamlitTableau
Reposted One Month AgoSaved
Remote
US
50K-63K Annually
Mid level
50K-63K Annually
Mid level
eCommerce • Insurance • Software
As a Fraud Operations Specialist, you will investigate fraud cases, analyze risk scores, collaborate across departments, and improve fraud detection processes. You will use data analysis to ensure compliance and support the overall efficiency of claims management.
Top Skills: ExcelGoogle SuiteMicrosoft SuiteSnowflakeSQL
Reposted One Month AgoSaved
Remote
US
124K-145K Annually
Senior level
124K-145K Annually
Senior level
eCommerce • Insurance • Software
Owns analytics and reporting that inform sales, merchant success, product, and fraud teams; builds business cases, pricing models, dashboards, and ROI analyses to drive merchant acquisition, expansion, and retention.
Top Skills: AISnowflakeSQLTableau
One Month AgoSaved
Remote
US
135K-165K Annually
Senior level
135K-165K Annually
Senior level
eCommerce • Insurance • Software
Lead end-to-end development of fraud and risk ML systems: define problems, engineer features, build and evaluate models, collaborate with product and engineering, deploy with ML engineers, and monitor production performance to detect drift and trigger retraining.
Top Skills: PythonPyTorchScikit-LearnSQLXgboost
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