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Data Science Graduate Jobs in California (NOW HIRING)

Triumph Arcade, Inc

Data Scientist

San Francisco, CA · On-site

$200K - $400K/yr

Qualifications * Bachelor's degree in a quantitative subject: math, physics, computer science ... Experience in competitive math, physics, or CS olympiads, or a graduate degree in a quantitative ...

Fieldguide

Lead Data Scientist

San Francisco, CA · On-site

$170K - $215K/yr

About the Role The Data Science team at Fieldguide leverages novel, proprietary datasets to build ... BA/BS in Computer Science, Engineering, Math/Statistics, Business, or a related field; a graduate ...

Tristar Insurance

Data Analyst I

Signal Hill, CA · On-site +1

$114K - $140K/yr

Whether you're a recent graduate or early in your career, this position offers a strong foundation in data science, data warehousing, and insurance analytics, with opportunities for growth and ...

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Data Science Graduate information

See California salary details

$37K

$121.1K

$193.9K

How much do data science graduate jobs pay per year?

As of Jun 22, 2026, the average yearly pay for data science graduate in California is $121,131.00, according to ZipRecruiter salary data. Most workers in this role earn between $97,200.00 and $134,200.00 per year, depending on experience, location, and employer.

What is the difference between Data Science Graduate vs Data Analyst?

AspectData Science GraduateData Analyst
Required CredentialsDegree in Data Science, Computer Science, or related fieldDegree in Statistics, Mathematics, or related field
Work EnvironmentInternships, entry-level roles in tech or finance companiesBusiness, marketing, or finance departments across industries
Employer & Industry UsageTech firms, startups, research institutionsCorporations, consulting firms, government agencies
Common Search & ComparisonYesYes

Data Science Graduates typically focus on building models, machine learning, and advanced analytics, often requiring programming skills and a strong foundation in data science concepts. Data Analysts primarily interpret data, generate reports, and support decision-making with statistical tools. While both roles analyze data, Data Science Graduates usually work on more complex modeling tasks, whereas Data Analysts focus on data interpretation and visualization.

What types of projects and responsibilities can a Data Science Graduate expect in their first role?

As a Data Science Graduate, you can expect to work on a variety of projects such as data cleaning, exploratory data analysis, and building predictive models under the guidance of senior team members. Typical responsibilities include preparing datasets, validating model outputs, and presenting findings to both technical and non-technical stakeholders. You’ll often collaborate with data engineers, software developers, and business analysts to ensure your solutions align with organizational goals. This early-career role is a great opportunity to learn industry-standard tools, gain mentorship, and build a portfolio of impactful projects.

What are the key skills and qualifications needed to thrive as a Data Science Graduate, and why are they important?

To thrive as a Data Science Graduate, you need strong analytical skills, a solid understanding of statistics, and proficiency in programming languages like Python or R, typically backed by a relevant degree. Familiarity with data visualization tools (e.g., Tableau), machine learning frameworks (e.g., scikit-learn, TensorFlow), and database management systems (e.g., SQL) is highly valuable. Strong communication, problem-solving, and adaptability help you convey insights and collaborate effectively with diverse stakeholders. These skills enable you to extract meaningful information from data, drive informed decisions, and add value to organizations in a data-driven world.

What are Data Science Graduates?

Data Science Graduates are individuals who have recently completed a degree or certification program in data science or a related field. They possess foundational knowledge in statistics, programming, and data analysis, and are equipped to apply these skills in real-world scenarios. These graduates are typically proficient in tools such as Python, R, SQL, and data visualization platforms, and are prepared for entry-level roles in data analytics, machine learning, or business intelligence. Their education often includes hands-on projects and internships to build practical experience. Data Science Graduates are in high demand across industries that rely on data-driven decision making.
What are popular job titles related to Data Science Graduate jobs in California? For Data Science Graduate jobs in California, the most frequently searched job titles are:
What job categories do people searching Data Science Graduate jobs in California look for? The top searched job categories for Data Science Graduate jobs in California are:
What cities in California are hiring for Data Science Graduate jobs? Cities in California with the most Data Science Graduate job openings:
Data Science Graduate jobs near you
Infographic showing various Data Science Graduate job openings in California as of June 2026, with employment types broken down into 3% As Needed, 75% Full Time, 19% Part Time, and 3% Contract. Highlights an 88% Physical, 3% Hybrid, and 9% Remote job distribution, with an average salary of $121,131 per year, or $58.2 per hour.

Data Scientist

Triumph Arcade, Inc

San Francisco, CA • On-site

$200K - $400K/yr

Full-time

Medical, Dental, Vision, Retirement

Posted 21 days ago

Job description

The Role
As a Data Scientist, you'll own the quantitative systems that drive how millions of real-money players experience Triumph's products, from their first session to long-term retention and monetization. You'll build the models and frameworks behind our most critical business decisions: how we price, how we pay out, how we match players, and how we grow.
You'd be joining a small, high-output quant team (4 people today) that operates like a trading desk. We build the mathematical systems that power Triumph's core business: pricing engines, payout distributions, matchmaking algorithms, risk models, and player behavior systems. Every model we ship touches real money and real users. You see the impact in the numbers the next day.
What You'll Do
  • Monetization & Pricing: Develop and optimize the pricing engines, payout structures, and edge calculations that are the mathematical backbone of Triumph's revenue. Own pack economics, rarity calibration, and pricing models for Rips by Triumph.
  • User Journey & Retention: Build models that map the full player lifecycle: acquisition, activation, engagement, monetization, churn risk. Identify the quantitative levers that move retention and LTV, and design interventions that act on them.
  • Experimentation: Design and analyze experiments (A/B tests and beyond) with rigorous statistical methodology. Own the measurement framework that tells us what's actually working across the product.
  • Behavioral Modeling: Develop ML and statistical models on rich, high-frequency user behavior data (session patterns, spend curves, matchmaking outcomes, gameplay trajectories) to drive both product decisions and real-time production systems.
  • Growth & Acquisition: Build models that directly inform acquisition spend and channel optimization, connecting upstream marketing decisions to downstream LTV and monetization outcomes.
  • Cross-Functional Impact: Partner closely with engineering, product, and leadership to translate model outputs into shipped features and strategic decisions. Identify high-leverage quantitative problems across the business and drive them from formulation to production impact.
Qualifications
  • Bachelor's degree in a quantitative subject: math, physics, computer science, statistics, economics, or a related discipline.
  • True depth and mastery in at least one quantitative domain: probability, statistics, applied ML, causal inference, or mathematics. We want spiky people who are confident they are among the best in their discipline.
  • Proficiency in Python and SQL.
  • Experience working with large-scale user or behavioral datasets.
Preferred Qualifications
  • Experience in consumer tech, gaming, fintech, or marketplace data science, particularly in monetization, LTV modeling, or experimentation.
  • Prior experience as a quantitative trader or quantitative researcher.
  • Experience in competitive math, physics, or CS olympiads, or a graduate degree in a quantitative discipline.
  • Nationally competitive in any activity. Some members of our team include national champions in debate, Clash Royale, and Poker.
Why Triumph?
  • High growth. Build a high-scale consumer platform that touches gaming, finance, and social with the autonomy to set our web direction.
  • High agency. Small, high-impact engineering team that is growing rapidly with significant opportunity for leadership and growth.
  • High energy. Passionate team who are proud of our work and velocity (16x year over year growth).
  • Competitive salary and benefits. $400/mo lunch credit, healthcare, vision, dental, 401k, etc.

Our team gathers 5 days a week at Triumph's headquarters at Levi's Plaza in San Francisco.

Apply