Top Data & Analytics Jobs in San Francisco, CA
As a Staff Data Scientist, the candidate will apply data science methods to our AI products, design datasets, promote evidence-based decision-making, and improve research and analytics processes through standardization and mentorship.
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As a Research Scientist at Databricks, you will advance deep learning techniques, create novel methodologies for training generative AI models, and work collaboratively with a diverse team to improve model capabilities and user accessibility to AI technologies.
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The Executive Researcher will lead top-of-funnel recruiting strategies for executive hiring, utilizing advanced search techniques to identify high-potential candidates in AI and tech industries. The role involves creating market maps, developing sourcing strategies, and collaborating with stakeholders to understand hiring needs while providing insights on industry trends and salary benchmarks.
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Lead a team of data scientists and engineers to develop innovative measurement products and data-driven solutions, ensure high-quality project delivery, and establish best practices for data science projects. Collaborate with multiple teams to enhance TV measurement and methodology while mentoring team members and advancing an inclusive culture.
As the Analytics Manager, you will lead a team of data analysts, develop and implement scalable reporting systems, and establish data governance processes. You will also oversee Business Intelligence initiatives, optimize workflows, and use data insights to drive organizational efficiency.
The Legal Support Analyst will assist attorneys and clients by generating reports, preparing documents for patent filings, monitoring deadlines, and managing files between the firm and other counsels. The role includes utilizing various legal databases and office applications to support patent-related tasks efficiently.
The Research Associate in Protein Sciences will engage in protein engineering projects, employing molecular biology techniques, conducting protein expression, purification, and characterization using biophysical methods. This role involves collaboration with teams to analyze data, prepare documentation, and optimize assays while maintaining laboratory compliance.
The MLOps Engineer will develop systems and APIs for inference and fine-tuning of large language models, implement runtime systems for production-level ML training, and collaborate with various teams for deploying and maintaining ML inference systems.
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The Principal Data Engineer will collaborate with data architects and business analysts to design data models, develop ELT processes, and solve production issues. Responsibilities include building efficient ETL pipelines, working with large data sets, and ensuring data accuracy and accessibility across organizations.
As a Lead Data Engineer at Stellic, you will design scalable architectures, build data pipelines, mentor teams, and drive alignment on engineering priorities while ensuring high-quality implementations.
Top Companies in San Francisco, CA Hiring Data + Analytics Roles
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