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Analytics Director Jobs in California (NOW HIRING)

Ivo

GTM & AI Analytics Director

San Francisco, CA · On-site

AI is both what you analyze and how you analyze. You'll measure how our AI products deliver value ... You'll partner with the Director of GTM Operations (who owns execution) and the Director of GTM ...

WelbeHealth

Director, Analytics

Los Angeles, CA · On-site

$159K - $211K/yr

The Director, Analytics partners with business and clinical leaders to solve complex operational and clinical challenges through data analysis, modeling, and strategic insights. This role combines ...

Everpure

Director, People Analytics

Santa Clara, CA · On-site

As Director, People Analytics, you will own the foundation - standing up a trusted data infrastructure, establishing the right metrics and governance, and then progressively layering insight ...

Everpure

Director, People Analytics

Santa Clara, CA · On-site

As Director, People Analytics, you will own the foundation - standing up a trusted data infrastructure, establishing the right metrics and governance, and then progressively layering insight ...

Highwire

Director, Insights & Analytics

San Francisco, CA · Hybrid

$110K - $150K/yr

The Director, Insights & Analytics plays a critical role in advancing Highwire's data-driven approach to strategic communications and digital marketing. This role is responsible for transforming ...

Highwire

Director, Insights & Analytics

San Francisco, CA · On-site

$110K - $150K/yr

The Director, Insights & Analytics plays a critical role in advancing Highwire's data-driven approach to strategic communications and digital marketing. This role is responsible for transforming ...

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Analytics Director information

See California salary details

$70.1K

$156K

$241.3K

How much do analytics director jobs pay per year?

As of Jul 29, 2026, the average yearly pay for analytics director in California is $156,045.00, according to ZipRecruiter salary data. Most workers in this role earn between $110,500.00 and $177,600.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as an Analytics Director, and why are they important?

To thrive as an Analytics Director, you need strong analytical abilities, expertise in statistical methods, advanced data modeling, and typically a degree in mathematics, statistics, computer science, or a related field. Familiarity with tools such as SQL, Python or R, data visualization platforms (e.g., Tableau, Power BI), and experience with big data systems are common requirements. Exceptional leadership, strategic thinking, and communication skills help drive cross-functional projects and translate complex data into actionable insights for stakeholders. These skills and qualities are essential to effectively lead analytics teams, influence business decisions, and deliver measurable value to the organization.

What does an Analytics Director do?

An Analytics Director leads a team responsible for analyzing data to inform business decisions and strategies. They oversee the collection, interpretation, and communication of data insights across departments, ensuring data-driven decision-making. Their role often includes developing analytics frameworks, managing data teams, setting key performance indicators, and collaborating with leadership to align analytics initiatives with organizational goals. Additionally, Analytics Directors help implement data governance policies and ensure analytics tools and techniques are effectively utilized.

What are some common challenges faced by an Analytics Director and how can they be addressed?

Analytics Directors often encounter challenges such as aligning analytics initiatives with overall business goals, managing and integrating data from multiple sources, and communicating complex findings to non-technical stakeholders. To address these, it's important to foster close collaboration with business leaders, invest in scalable data infrastructure, and develop strong communication skills within the analytics team. Building a culture of data-driven decision-making and continuous learning also helps overcome these obstacles and ensures the analytics function delivers real value.

What is the difference between Analytics Director vs Data Scientist?

AspectAnalytics DirectorData Scientist
Required CredentialsBachelor's or Master's in Business, Analytics, or related fields; often prefers experience over certificationsBachelor's or Master's in Computer Science, Statistics, or related fields; may have certifications like Certified Analytics Professional
Work EnvironmentLeads analytics teams, collaborates with executives, oversees strategyAnalyzes data, builds models, and develops algorithms, often working independently or in small teams
Employer & Industry UsageCommon in corporate, finance, marketing, and consulting firmsFound in tech companies, research institutions, and data-driven industries

The Analytics Director focuses on leading analytics strategies and managing teams, while Data Scientists primarily analyze data and develop models. Both roles require strong analytical skills, but the Director has a broader leadership and strategic focus.

What Does an Analytics Director Do?

An analytics director oversees the data analytics and data warehousing departments at a company. As an analytics director, you take the lead on all data analytics systems and ensure your department aligns with the company’s priorities. You research and develop strategies to improve the analytics of your company. You collaborate with your team along with other members of your company’s senior leadership to influence data capabilities and competencies in the company. Your responsibilities include adopting appropriate tools and software to drive innovation. Other duties include staying informed on the latest industry trends in data analytics.

More about Analytics Director jobs
What are the most commonly searched types of Analytics jobs in California? The most popular types of Analytics jobs in California are:
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What job categories do people searching Analytics Director jobs in California look for? The top searched job categories for Analytics Director jobs in California are:
What cities in California are hiring for Analytics Director jobs? Cities in California with the most Analytics Director job openings:
What are popular job titles related to Analytics Director jobs in CA? For Analytics Director jobs in CA, the most frequently searched job titles are:
Analytics Director jobs near you
Infographic showing various Analytics Director job openings in California as of July 2026, with employment types broken down into 1% Internship, 91% Full Time, 5% Part Time, 1% Temporary, and 2% Contract. Highlights an 79% Physical, 5% Hybrid, and 16% Remote job distribution, with an average salary of $156,045 per year, or $75 per hour.
GTM & AI Analytics Director

GTM & AI Analytics Director

Ivo

San Francisco, CA • On-site

Full-time

Posted 9 days ago

Job description

Why join Ivo?
Every civilization runs on the same infrastructure: agreements between people who don't fully trust each other. Sumerians pressed them into clay. Romans carved them into stone. We bury them in 80-page PDFs.
The way those agreements are reviewed hasn't changed in four thousand years - a human reads the whole thing and tries not to miss anything. We're building the AI that finally changes that. Ivo is the contract intelligence platform of choice for companies like Uber, Meta, Canva, IBM, and Shopify. We recently raised our Series B and have grown 800% over the last 12 months.
What is the job?
What does "usage" mean when the product works autonomously? How do we measure value delivered vs. sessions logged? What's the leading indicator of expansion when the user isn't clicking, but its agent is?
AI is both what you analyze and how you analyze. You'll measure how our AI products deliver value to customers, and you'll use AI tools to do that measurement faster and deeper than any traditional analytics team could.
You're the person who tells us why a number moved and what to do about it. Pipeline slowing? You diagnose the stage, segment, and rep-level bottleneck before anyone asks. Expansion stalling? You build the propensity model, identify the white space, and hand the VP of CSM prioritized target list.
This isn't a traditional analytics role. Ivo builds AI products that interact with customers in ways that didn't exist a few years ago: autonomous contract review, LLM-powered intelligence queries, API-driven workflows. The old playbook for measuring engagement (DAU/MAU, feature clicks, time-in-app) doesn't fully apply when an AI agent does the work and the human reviews the output. You'll need to invent new frameworks for measuring business impact when the product thinks, acts, and delivers value without a user sitting in a UI. If that problem excites you, keep reading.
Reporting to the VP Revenue Strategy & Operations, you'll own GTM analytics end-to-end: pipeline health and velocity, forecast modeling, win/loss analysis, rep productivity, territory performance, expansion propensity, churn risk - and the product usage metrics that connect how customers interact with our AI to whether they renew, expand, and advocate. You'll partner with the Director of GTM Operations (who owns execution) and the Director of GTM Systems & Automation (who owns infrastructure), and the tech team, translating data into action.
As pricing evolves toward usage-based and API consumption models, and eventually outcome models, you'll build consumption analytics: product telemetry linked to revenue, activation cohorts, retention curves, and expansion triggers. You quantify the ROI of strategic bets before we make them.
What you bring
  • AI-native workflow. You use Claude, ChatGPT, Cursor daily as your analytical operating system. You prototype by prompting before you code. You generate SQL, debug logic, draft executive summaries, and pressure-test your own models with AI. You have opinions on which tools are better for which tasks.
  • 5-10 years in GTM analytics, strategy consulting, or revenue analytics at a high-growth B2B SaaS company. You know which metrics matter at each stage from $10M→$100M.
  • Management consulting foundation (MBB or equivalent).
  • Intellectual curiosity about how AI-native products change measurement. You're not satisfied applying last generation's engagement metrics to a product where AI agents do the heavy lifting.
  • Product analytics depth. You've worked with product telemetry data: activation funnels, feature adoption, retention cohorts - and connected it to revenue outcomes. You partner with Product and Data Engineering to define the instrumentation that matters, not just consume what's already tracked.
  • Deep SaaS fluency: ARR, NDR, pipeline velocity, cohort LTV, CAC payback. You think in unit economics and systems, not charts.
  • Strong SQL. Production queries against BigQuery or Snowflake, dbt models, dashboards in Looker or equivalent. You're hands-on, and you don't need a data engineer to unblock your path to output.
  • Quantitative modeling: forecasting, account scoring, predictive churn, scenario analysis. You've built models that influenced real resource allocation decisions, not just slide decks.
  • End-to-end pipeline analysis: lead to close to renewal to expansion. You identify bottlenecks, quantify leakage, and deliver recommendations that change behavior.
  • Board-level communication. You present complex analysis to the CEO and board in clear, actionable terms. You know the difference between a data readout and a strategic recommendation.
  • You ship fast. AI copilots mean you operate at 3x traditional output and invest the time saved in deeper thinking and higher quality insights, not more dashboards.
  • STEM or BS in Finance, Economics

Bonus points
  • Built or deployed AI/LLM-powered analytics workflows - anomaly detection, natural language querying, agent-based reporting.
  • Defined new engagement or value metrics for AI-native products where traditional product analytics frameworks didn't apply.
  • Product analytics tools (Mixpanel, PostHog) linked to revenue outcomes.
  • Account scoring or health scoring models operationalized into CRM workflows.
  • Usage-based or consumption revenue model experience.
  • Side projects, blog, or open-source contributions in AI-augmented analytics.
  • MBA or a graduate degree in analytical field

What does success look like?
In 90 days: Self-serve dashboards live - Sales, CS, and Marketing answer their own questions. Weekly executive metrics automated. Leadership has pipeline and forecast visibility they trust for the first time. At least one recurring analysis replaced with an AI-automated workflow. Product analytics baseline established - you've defined what "healthy usage" means for an AI-native product and can explain why.
In 12 months:
  • GTM planning is analytically rigorous - targets, coverage guides, capacity models, territory design all data-backed and pressure-tested.
  • Expansion analytics operational: white space mapped, health scores validated, propensity models driving prioritization.
  • Product analytics are a competitive advantage - you've built measurement frameworks that capture value delivery in ways our competitors haven't figured out yet, and those frameworks directly inform pricing, packaging, and expansion strategy.
  • You've built quantitative models that directly influenced strategic investments.
  • We make GTM decisions on data - surfaced faster because AI does the heavy lifting and you do the thinking.

Apply