Top Data Science Jobs in San Francisco, CA
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Senior Data Scientist role at Square focused on leveraging data science techniques to improve incremental revenue generation. Responsibilities include understanding data ecosystem, supporting revenue forecasting models, partnering with ML engineers, driving insights with analytics, and mentoring team members.
The Senior Credit Risk Analyst will leverage advanced data analytics to optimize credit strategies, develop evaluation frameworks for the credit ecosystem, assist in product pricing strategy, run A/B tests, and collaborate with various teams to enhance credit portfolio performance.
As a Senior Associate in AI & GenAI Data Science at PwC, you will leverage analytical techniques to extract insights from data, build AI/GenAI solutions, and collaborate with clients to understand and address their business challenges. Responsibilities include model development, data processing, and managing client engagements to deliver high-quality results.
As a Senior Manager at PwC Intelligence, you will support service and market leaders to enhance operations, identify new opportunities through market analysis, and contribute to service offerings. You will lead teams to solve complex business issues while fostering a collaborative environment and maintaining the firm's ethical standards.
The Applied Researcher I at Capital One will collaborate with cross-functional teams to develop AI-powered products. Responsibilities include utilizing a variety of technologies to analyze large data sets, building AI models through their entire lifecycle, and conducting impactful applied research to enhance customer experiences.
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Lead end-to-end development life cycle of innovative ML-based enterprise products, architect and implement AI-enabled data products, research and assess state-of-the-art AI algorithms, engage with senior client leaders, publish thought leadership pieces, foster ZS talent, shape firm strategy in newer areas and practices including AI.
The Principal Engineer will lead efforts in machine learning and AI, collaborating with teams to build impactful products, setting technical standards, and mentoring others. Responsibilities include hands-on development, technical leadership, and influencing hiring and coding practices.
As a Principal Applied Scientist, you will lead the delivery of AI products, collaborate with ML engineers, improve data quality and usability, and engage in public-facing content to enhance Xero's profile. The role requires a focus on creating impactful, customer-facing ML and AI solutions while emphasizing high-quality code from the outset.
The Senior Data Scientist at Cash App will analyze large datasets using SQL and programming languages to provide actionable insights. Responsibilities include working on product analytics, designing A/B tests, collaborating with engineers on data logging, forecasting metrics for business strategies, and creating data visualizations and dashboards for stakeholders.
As a Senior Data Scientist at Snap Inc, you'll leverage your expertise in quantitative analysis and data modeling to derive actionable insights and optimize product development. Collaborating cross-functionally with product managers, engineers, and designers, you'll conduct statistical analyses and build predictive models to drive informed decision-making. This role involves crafting metrics and dashboards to communicate insights effectively and initiating projects aimed at discovering new opportunities within the company's data framework.
The Director of Data Science and Machine Learning will lead the Machine Learning, Data Science, and Product Analytics teams, drive data-powered insights for product performance, and collaborate across departments to optimize business growth. Responsibilities include team leadership, defining strategic vision, fostering collaboration, and overseeing the development of ML and DS models.
As a Data Scientist at Kikoff, you will leverage your analytical skills to drive product development by using data-driven insights. Your role includes shaping product goals, conducting rigorous analyses, and effectively communicating data stories to cross-functional teams to enhance customer financial security.
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