Top Data & Analytics Jobs in San Francisco, CA
As a Data Scientist, you will analyze large datasets to enhance the understanding of email attack patterns, evaluate detection product quality, experiment with solutions, and generate insights for internal teams and partners to improve cyber security products.
The Manager, Data Engineering will lead a team responsible for maintaining and building data infrastructure that supports product features and analytics. Responsibilities include architecting solutions, mentoring the team, building reports, and managing data resources, ensuring the system is scalable and reliable.
The Inventory Planner is responsible for managing and optimizing inventory across various channels and vendor partners. They will create purchasing forecasts, support inventory strategies, communicate weekly reports, track inventory levels, ensure ERP accuracy, and collaborate with finance and operational teams to improve inventory efficiency and meet supply targets.
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The Lead Data Engineer will design and expand Nuna's Data Platform, establish best practices, mentor team members, and collaborate with data scientists to optimize workflows. This role entails hands-on development, managing complex data sources, and ensuring data governance while contributing to innovative projects in healthcare.
The Operations Analyst's goal is to enhance efficiencies and quality within operations through analysis, process design, and project management. Responsibilities include conducting efficiency and financial analyses, managing client projects, and improving internal processes while learning from senior partners and engaging with multiple departments.
The SAP Functional Analyst will facilitate design workshops, write specifications for enhancements, configure SAP PM and PS functionalities, and develop test scripts to support various testing processes.
The Lead Data Engineer will develop and optimize data infrastructure, build scalable ETL pipelines, manage data warehouses and lakehouses, ensure data quality, and collaborate with data science teams to support ML model deployment.
Looking for a Data Engineer with 5+ years of experience in a SaaS environment. Must be proficient in SQL, dbt, Python, and have experience with data engineering tools and cloud services. Responsibilities include owning data workflows, ensuring data quality, and leading data modeling efforts.
As a Principal Machine Learning Engineer, you will lead a team to develop innovative deep learning vision algorithms for robotic grasping. Responsibilities include designing machine learning models, collaborating with engineers, and ensuring effective interaction between robots and their environment.
The Quantitative Scientist will work closely with clinical data to solve complex real-world problems in healthcare. Responsibilities include data cleaning, modeling, inference, and interpretation to support commercial projects, leveraging real-world data across therapeutic areas like urology and ophthalmology.
Top Companies in San Francisco, CA Hiring Data + Analytics Roles
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