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Data Strategist Jobs in California (NOW HIRING)

DYNA Robotics Inc

AI Data Strategist

Redwood City, CA · On-site

$148K - $192K/yr

The Role We are hiring an AI Data Strategist to define the data requirements that drive model improvement across Dyna's robotics platform. This is a senior individual contributor role that focuses on ...

Dyna Robotics

AI Data Strategist

Redwood City, CA · On-site

$148K - $192K/yr

They are seeking an AI Data Strategist to define the data requirements for model improvement across their robotics platform, focusing on strategy rather than operational execution. Responsibilities ...

Dyna Robotics

AI Data Strategist

Redwood City, CA · On-site

$148K - $192K/yr

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 ...

Esri

Sr. Marketing Data Strategist

Redlands, CA · On-site

Overview Are you a strategic, data driven professional who excels at bringing clarity to complex data? As a Sr. Marketing Data Strategist, you will leverage advanced expertise in marketing data ...

Esri

Sr. Marketing Data Strategist

Redlands, CA · On-site

They are seeking a Sr. Marketing Data Strategist who will leverage expertise in marketing data analysis, modeling, governance, and enrichment to improve data quality frameworks and enhance strategic ...

Esri

Sr. Marketing Data Strategist

Redlands, CA · On-site

$93K - $156K/yr

Overview Are you a strategic, data driven professional who excels at bringing clarity to complex data? As a Sr. Marketing Data Strategist, you will leverage advanced expertise in marketing data ...

Amgen

Director, Strategic Data Lead

Thousand Oaks, CA · On-site

This role brings Commercial Data Strategy perspective into business, brand, and data planning discussions, shaping data strategy while partnering with the teams that generate insights, build ...

Wasserman Media

Project Manager, Data Strategy

Los Angeles, CA · On-site

$55.75 - $75.50/hr

The Data Strategy group is responsible for the data modernization of all data capabilities across the THE • TEAM's portfolio. We lead THE • TEAM's efforts in building a solid data foundation and ...

AbbVie

Data Strategy Lead - Hybrid

Irvine, CA · On-site

$109K/yr

The Clinical Data Strategy and Operations (CDSO) Data Strategy Lead serves as the study start-up domain expert and key strategic partner to the clinical study team, owning all data-related study ...

Teamwass

Project Manager, Data Strategy

Los Angeles, CA · On-site

$55.75 - $75.50/hr

The Data Strategy group is responsible for the data modernization of all data capabilities across the THETEAM's portfolio. We lead THETEAM's efforts in building a solid data foundation and optimizing ...

AbbVie

Data Strategy Lead - Hybrid

Irvine, CA · Hybrid

Purpose: ​​The Clinical Data Strategy and Operations (CDSO) Data Strategy Lead serves as the study start-up domain expert and key strategic partner to the clinical study team, owning all data ...

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All JobsData Strategist JobsData Strategist Jobs in California

Data Strategist information

See California salary details

$44.4K

$138K

$175.2K

How much do data strategist jobs pay per year?

As of Aug 7, 2026, the average yearly pay for data strategist in California is $138,035.00, according to ZipRecruiter salary data. Most workers in this role earn between $119,900.00 and $154,900.00 per year, depending on experience, location, and employer.

How much does a data strategist make?

The average salary for a data strategist typically ranges from $70,000 to $130,000 annually, depending on experience, industry, and location. Senior roles or those with specialized skills in data analysis and strategy can earn higher compensation, often exceeding $150,000. Salaries may also include bonuses and benefits based on performance and company size.

What are the key skills and qualifications needed to thrive as a data strategist?

To thrive as a Data Strategist, you need strong analytical skills, experience with data modeling and interpretation, and typically a background in statistics, computer science, or a related field. Familiarity with data visualization tools (such as Tableau or Power BI), database systems (like SQL), and knowledge of data governance frameworks are essential. Excellent communication, problem-solving abilities, and strategic thinking help you translate complex data insights into actionable business recommendations. These skills are crucial for aligning data initiatives with organizational goals and driving informed decision-making.

What is a data strategist?

A Data Strategist is a professional who designs and implements data-driven strategies to help organizations achieve their goals. They analyze business needs, identify opportunities to leverage data, and develop plans for collecting, managing, and utilizing data effectively. Data Strategists often collaborate with data analysts, engineers, and business leaders to ensure data initiatives align with overall organizational objectives. Their role is crucial in transforming raw data into actionable insights that drive decision-making and business growth.

How does a data strategist typically collaborate with other departments to drive business outcomes?

A Data Strategist works closely with cross-functional teams such as marketing, product development, IT, and executive leadership to align data initiatives with organizational goals. They often facilitate workshops, lead data-driven decision-making meetings, and translate complex analytics into actionable business strategies. By serving as a bridge between technical teams and business stakeholders, Data Strategists ensure that data insights are effectively integrated into company-wide processes and strategies. This collaborative approach is essential for maximizing the impact of data on business outcomes.
What are popular job titles related to Data Strategist jobs in California? For Data Strategist jobs in California, the most frequently searched job titles are:
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What cities in California are hiring for Data Strategist jobs? Cities in California with the most Data Strategist job openings:
Data Strategist jobs near you
Infographic showing various Data Strategist job openings in California as of August 2026, with employment types broken down into 5% Internship, and 95% Full Time. Highlights an 89% In-person, and 11% Remote job distribution, with an average salary of $138,035 per year, or $66.4 per hour.

AI Data Strategist

DYNA Robotics Inc

Redwood City, CA • On-site

$148K - $192K/yr

Full-time

Re-posted 18 days ago

Job description

Dyna Robotics builds general-purpose robots powered by a proprietary embodied AI foundation model with top-in-industry generalization and real-world performance. Already deployed with customers across multiple industries, our robots do commercial-grade work in the physical world. Our team comes from Google DeepMind, Meta, and Cruise, and we're backed by CRV, First Round, and other leading investors.
The Role
We are hiring an AI Data Strategist to define the data requirements that drive model improvement across Dyna's robotics platform.
This is a senior individual contributor role that focuses on strategy rather than managing operational execution. Instead of running the day-to-day data pipeline, you will define what operations and research execute against. You will establish the specifications, frameworks, and feedback loops that determine whether our data actually improves our models.
The core question you will help answer every week is: our model failed here, so what does that mean for our data strategy?
What You'll Do
  1. 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.
  2. 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.
  3. 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.
  4. 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.

Who You Are
  • Systems Thinker: You understand that superior models come from exceptional data strategy, not just massive data volume.
  • Structured Problem Solver: Highly analytical and detail-oriented, with the ability to translate messy, real-world failures into structured frameworks.
  • Analytically Minded: Possess strong instincts for failure analysis, dataset structure, and the feedback loops between deployment and training.
  • Cross-Functional Influencer: Able to rally and influence cross-functional teams without needing direct authority.
  • Clear Communicator: Strong written and verbal communication skills, with the ability to prioritize effectively in fast-moving environments where everything feels urgent.
What You'll Bring
  • Core Experience: 4-8+ years of experience working in AI/ML, robotics, autonomy, or data-centric systems roles.
  • Data Strategy Expertise: Proven experience defining data quality standards, evaluation frameworks, annotation systems, or data strategy for machine learning products.
  • Collaborative Track Record: Experience working closely with cross-functional teams, including ML researchers, operations, annotation teams, and engineering.
  • Edge-Case Proficiency: A deep understanding of how deployment failures, edge cases, and real-world operational data translate into model training and evaluation improvements.
Bonus points for
  • 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.

Apply