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Manager Of Data Science Jobs in California (NOW HIRING)

As Director, you will lead a team of data scientists and managers, setting the vision for how data shapes strategy across Figma's AI products. You'll work closely with Product, Engineering, Design ...

Manager, Data Science

San Francisco, CA ยท On-site

$221K - $320K/yr

Join the Future of Commerce with Whatnot! Whatnot is the largest live shopping platform in North ... Role We're looking for a Manager, Data Science to lead a high-impact team working on core ...

Lead and develop a team of data scientists responsible for high-impact analytics, predictive ... You have experience managing and developing data scientists or analysts and know how to set a high ...

Adidev Technologies is seeking 1-2 yrs of relevant experience in Data Science. A project can last anywhere from 6 months to 18 months. Salary varies depending on experience, and we are in search of ...

Adidev Technologies is seeking 1-2 yrs of relevant experience in Data Science. A project can last anywhere from 6 months to 18 months. Salary varies depending on experience, and we are in search of ...

As part of the Data Science and Engineering team, this role combines strategic leadership, technical expertise, and people management to deliver innovative data solutions while ensuring robust ...

As part of the Data Science and Engineering team, this role combines strategic leadership, technical expertise, and people management to deliver innovative data solutions while ensuring robust ...

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Manager Of Data Science information

See California salary details

$30.6K

$95.9K

$169.7K

How much do manager of data science jobs pay per year?

As of Aug 16, 2026, the average yearly pay for manager of data science in California is $95,873.00, according to ZipRecruiter salary data. Most workers in this role earn between $65,100.00 and $123,900.00 per year, depending on experience, location, and employer.

What is the difference between Manager Of Data Science vs Data Scientist?

AspectManager Of Data ScienceData Scientist
Required CredentialsBachelor's or Master's in Data Science, Statistics, or related field; often leadership experienceBachelor's or Master's in Data Science, Statistics, or related field; strong technical skills
Work EnvironmentOversees teams, manages projects, collaborates with stakeholdersFocuses on data analysis, model development, and technical problem-solving
Employer & Industry UsageUsed in organizations with data teams, analytics departmentsCommonly employed in tech, finance, healthcare, and research sectors

The main difference between a Manager Of Data Science and a Data Scientist is the level of responsibility. Managers oversee teams and strategic initiatives, while Data Scientists focus on technical data analysis and model building. Both roles require strong analytical skills, but the Manager role emphasizes leadership and project management.

How does a manager of data science typically balance hands-on technical work with team leadership responsibilities?

A Manager of Data Science often divides their time between overseeing project execution and supporting their team's professional growth. While they may still participate in high-level technical decision-making and occasionally contribute to code or modeling, much of their focus shifts to setting strategic direction, mentoring team members, and facilitating cross-functional collaboration. They are responsible for ensuring that projects align with business goals, providing technical guidance, and creating an environment where data scientists can thrive. Effective managers also spend time communicating with stakeholders to translate business needs into actionable data projects.

What are the key skills and qualifications needed to thrive as a manager of data science, and why are they important?

To thrive as a Manager of Data Science, you need advanced expertise in data analytics, machine learning, and statistical modeling, typically backed by a degree in a quantitative field and prior experience in data science roles. Familiarity with tools like Python, R, SQL, cloud platforms (e.g., AWS, Azure), and project management systems is essential, and certifications such as Certified Analytics Professional (CAP) can be valuable. Strong leadership, communication, and problem-solving skills help in guiding teams, translating business needs into data solutions, and fostering collaboration. These skills and qualities are crucial for delivering actionable insights, driving innovation, and ensuring successful data-driven strategies in complex organizational environments.

What is a manager of data science?

A Manager of Data Science is a leadership role responsible for overseeing a team of data scientists and analysts, guiding data-driven projects, and ensuring that business objectives are met through data analysis and modeling. They collaborate with stakeholders to identify business needs, design analytical solutions, and manage the end-to-end process of extracting insights from large datasets. In addition to technical expertise, this role requires strong leadership, project management, and communication skills to translate complex findings into actionable strategies.

What are the most commonly searched types of Of Data Science jobs in California?

The most popular types of Of Data Science jobs in California are:

What cities in California are hiring for Manager Of Data Science jobs?

Cities in California with the most Manager Of Data Science job openings:

Head of Data Science - Document Verification & Biometrics

Socure

San Francisco, CA โ€ข On-site

Full-time

Re-posted 8 days ago


Job description

Job Summary:
Socure is building the identity trust infrastructure for the digital economy, and they are seeking a leader to drive AI-powered Document Verification and Biometrics solutions. This role involves owning the data science strategy and execution, leading a team, and advancing fraud detection capabilities.
Responsibilities:
โ€ข Own and define the data science vision for Document Verification, Biometrics, and Reusable ID, delivering step-function improvements in accuracy, speed, and user experience.
โ€ข Lead and scale a high-performing team of data scientists and applied researchers, setting a high standard for execution, innovation, and accountability.
โ€ข Architect and deploy state-of-the-art computer vision and multimodal systems, including vision-language models (VLMs), for document understanding, face matching, liveness detection, and identity verification.
โ€ข Drive the development of domain-specific foundation models tailored to identity, documents, and biometrics, leveraging large-scale proprietary datasets.
โ€ข Lead the transition to agentic systems, building intelligent agents that can reason over document and biometric signals, automate verification workflows, and adapt dynamically to new fraud patterns.
โ€ข Advance fraud and attack detection capabilities, including deepfake detection, presentation attack detection, and counterfeit document detection.
โ€ข Design and implement secure and robust systems resilient to emerging threats such as prompt injection and adversarial attacks on multimodal and agent-based systems.
โ€ข Leverage vector databases and embedding systems to power similarity search, identity linking, and reusable identity experiences.
โ€ข Partner closely with Product, Engineering, and Risk teams to deliver scalable, production-grade solutions that meet both business and regulatory requirements.
โ€ข Drive rapid experimentation and deployment, balancing innovation with reliability, explainability, and compliance.
โ€ข Own customer communication and stakeholder management, serving as a trusted technical leader in engagements with customers, partners, and internal stakeholders; clearly articulate model behavior, agentic systems, performance trade-offs, and roadmap decisions while building strong, long-term relationships.
โ€ข Represent Socure externally as a thought leader in biometrics, document AI, and fraud prevention.
Qualifications:
Required:
โ€ข Advanced degree (MS/PhD preferred) in Computer Science, Electrical Engineering, Machine Learning, or a related field.
โ€ข 10+ years of experience in data science, machine learning, or applied AI, with a strong track record of building and deploying production systems.
โ€ข Deep expertise in computer vision and multimodal AI, including experience with vision-language models (VLMs).
โ€ข Proven experience building domain-specific foundation models or large-scale representation learning systems.
โ€ข Strong understanding of biometric systems, including face recognition, liveness detection, and anti-spoofing techniques.
โ€ข Experience detecting and mitigating deepfakes, presentation attacks, and counterfeit documents.
โ€ข Strong understanding of agentic system design, including agent skills, orchestration/harness frameworks, and real-world deployment of autonomous or human-in-the-loop agents.
โ€ข Experience with vector databases and embedding-based retrieval systems.
โ€ข Strong awareness of emerging attack vectors, including prompt injection, adversarial inputs, and model exploitation techniques.
โ€ข Proven ability to lead and scale high-performing teams while delivering under ambiguity and tight timelines.
โ€ข Proficiency in Python and modern ML frameworks (e.g., PyTorch).
โ€ข Proven ability to engage with customers and external stakeholders, clearly explaining complex AI systems, trade-offs, and outcomes to both technical and non-technical audiences.
Preferred:
โ€ข Experience representing organizations in customer-facing discussions, executive briefings, or public speaking engagements is strongly preferred.
Company:
Socure is a predictive analytics platform for digital identity verification of consumers. Founded in 2012, the company is headquartered in Incline Village, USA, with a team of 501-1000 employees. The company is currently Late Stage.