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Data Strategy Jobs in California (NOW HIRING)

Dyna Robotics

AI Data Strategist

Redwood City, CA · On-site

$148K - $192K/yr

... strategy over operational execution. Responsibilities : • Define Data Collection Priorities • Identify lifecycle gaps: Maintain a clear, comprehensive view of where the data lifecycle has gaps ...

SwiftCruit

Director, Strategic Data Lead

Thousand Oaks, CA · On-site

$199.06 - $269.32/hr

Communicate data strategy, recommendations, trade‑offs, and decision points clearly to senior stakeholders across the business teams. What we expect of you The dynamic professional we seek is ...

Esri

Sr. Marketing Data Strategist

Redlands, CA · On-site

Data governance, data strategy enablement, & process optimization. Partner with digital marketing, technology, and legal/privacy teams to ensure audience strategies are supported by compliant ...

Esri

Sr. Marketing Data Strategist

Redlands, CA · On-site

Required : • 8+ years of experience in marketing data, analytics, data strategy, or related fields • Strong expertise in data models, segmentation strategy, data quality, governance, and ...

SwiftCruit

Principal Data Strategy Manager

Pleasanton, CA · On-site

$130.70 - $261.30/hr

Abbott is a global healthcare leader that helps people live more fully at all stages of life. Our portfolio of life-changing technologies spans the spectrum of healthcare, with leading businesses and ...

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All JobsData Strategy JobsData Strategy Jobs in California

Data Strategy information

See California salary details

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$111.5K

$207.1K

How much do data strategy jobs pay per year?

As of Aug 9, 2026, the average yearly pay for data strategy in California is $111,473.00, according to ZipRecruiter salary data. Most workers in this role earn between $81,276.00 and $141,988.00 per year, depending on experience, location, and employer.

What is a data strategy?

A Data Strategy job focuses on defining and implementing an organization's approach to data management, governance, and utilization. Professionals in this role ensure that data is aligned with business goals, enabling better decision-making and competitive advantage. They work on data policies, frameworks, and analytics strategies while collaborating with stakeholders across IT, business, and data teams. The role often involves assessing data quality, strategic planning for data infrastructure, and identifying opportunities for data-driven innovation.

What are some typical projects or initiatives a data strategy professional works on?

Data Strategy professionals often lead projects related to developing enterprise data roadmaps, improving data quality standards, implementing data governance frameworks, and aligning analytics initiatives with business objectives. They may be involved in launching new data platforms, advising on data privacy compliance, or collaborating on cross-functional teams to ensure data is effectively leveraged for decision-making. The role usually requires partnering with IT, analytics, and business units to coordinate efforts and ensure alignment with organizational priorities.

What does a data strategist do?

A data strategist develops and implements plans to collect, analyze, and utilize data to support business goals. They identify data needs, establish data governance standards, and work with teams to ensure data-driven decision-making using tools like analytics platforms and data management systems.

What are the key skills and qualifications needed to thrive in data strategy?

To thrive in Data Strategy, you need strong analytical skills, business acumen, experience with data governance, and typically a degree in data science, analytics, or a related field. Familiarity with tools such as SQL, BI platforms (like Tableau or Power BI), and data management systems, along with certifications such as CDMP or DAMA, are often required. Excellent communication, stakeholder management, and problem-solving skills set top professionals apart in this domain. These abilities are vital for bridging technical and business teams to drive actionable strategies and maximize data-driven value for organizations.

What does a data strategy do?

A data strategy defines how an organization manages, uses, and governs its data to support business goals. A data strategist develops plans for data collection, storage, quality, security, and analytics, often utilizing tools like data management platforms and analytics software. This role ensures data is accurate, accessible, and aligned with organizational priorities.
What are the most commonly searched types of Data Strategy jobs in California? The most popular types of Data Strategy jobs in California are:
What are popular job titles related to Data Strategy jobs in California? For Data Strategy jobs in California, the most frequently searched job titles are:
What job categories do people searching Data Strategy jobs in California look for? The top searched job categories for Data Strategy jobs in California are:
What cities in California are hiring for Data Strategy jobs? Cities in California with the most Data Strategy job openings:
Data Strategy jobs near you
Infographic showing various Data Strategy job openings in California as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 21% Part Time, 2% Temporary, and 3% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $111,473 per year, or $53.6 per hour.

AI Data Strategist

Dyna Robotics

Redwood City, CA • On-site

$148K - $192K/yr

Full-time

Re-posted 20 days ago

Job description

Job Summary:
Dyna Robotics is a company focused on creating general-purpose robots powered by advanced AI technology. They are seeking an AI Data Strategist to define data requirements that enhance model improvement across their robotics platform, emphasizing strategy over operational execution.
Responsibilities:
• Define Data Collection Priorities
• Identify lifecycle gaps: Maintain a clear, comprehensive view of where the data lifecycle has gaps, from pre-training through post-training.
• Direct collection efforts: Prioritize what the data collection team should focus on next, clearly distinguishing between data that merely adds volume and data that actually drives model performance.
• Design Evaluation & Quality Frameworks
• Set the standard: Define how robot episodes should be labeled and determine what rubrics and taxonomies capture meaningful signal.
• Establish quality benchmarks: Define what "good data" looks like for each task and model stage so the labeling team can execute flawlessly against your standards.
• Extract Signal from Operations
• Translate field realities: Partner closely with the operations team to understand what is happening in the field, including shift handoffs, collection quality, and deployment issues.
• Inform data strategy: Act as a strategic consumer of operations output, translating real-world operational realities into high-impact data strategy decisions without directly managing the operations team.
• Build Data Lifecycle Observability
• Define health metrics: Establish the metrics that measure the health of each phase of the data pipeline, including collection coverage, label quality, evaluation consistency, and model feedback loops.
• Drive visibility: Create a real-time, organization-wide view of data lifecycle health.
Qualifications:
Required:
• 4-8+ years of experience working in AI/ML, robotics, autonomy, or data-centric systems roles.
• Proven experience defining data quality standards, evaluation frameworks, annotation systems, or data strategy for machine learning products.
• Experience working closely with cross-functional teams, including ML researchers, operations, annotation teams, and engineering.
• A deep understanding of how deployment failures, edge cases, and real-world operational data translate into model training and evaluation improvements.
Preferred:
• Experience operating in fast-moving, ambiguous startup or R&D-heavy environments.
• Experience with embodied AI, video, or time-series data.
• Familiarity with evaluation pipelines, active learning, or data-centric AI.
• Exposure to annotation tooling such as Labelbox, Scale, CVAT, Encord, or Voxel51.
Company:
Dyna Robotics develops advanced robotic manipulation models to automate repetitive and stationary tasks. Founded in 2024, the company is headquartered in Redwood City, USA, with a team of 11-50 employees. The company is currently Early Stage.

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