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Quantitative Modeling Jobs in Berkeley, CA (NOW HIRING)

Your expertise in quantitative modeling, experimentation and algorithms will be utilized to solve some of the most complex engineering challenges at the company. You will collaborate on a wide array ...

Strong analytical skills and comfort working with quantitative models. * Ability to collaborate across teams and learn new system domains quickly. Preferred Skills * Exposure to AI/ML workloads or ...

Your expertise in quantitative modeling, experimentation and algorithms will be utilized to solve some of the most complex engineering challenges at the company. You will collaborate on a wide array ...

This role is designed for an analyst who is proficient in data visualization and quantitative modeling, looking to apply their skills within a fast-paced, enterprise environment. You will act as a ...

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Quantitative Modeling information

See Berkeley, CA salary details

$120.2K

$208.2K

$318.3K

How much do quantitative modeling jobs pay per year?

As of Aug 22, 2026, the average yearly pay for quantitative modeling in Berkeley, CA is $208,187.00, according to ZipRecruiter salary data. Most workers in this role earn between $165,000.00 and $244,100.00 per year, depending on experience, location, and employer.

What is a quantitative modeling?

A Quantitative Modeling job involves using mathematical, statistical, and computational techniques to analyze data and construct models that help businesses make informed decisions. Professionals in this field work in finance, risk management, economics, and other industries to develop predictive models, optimize strategies, and assess uncertainties. They often use programming languages like Python, R, or MATLAB, along with machine learning and statistical methods, to solve complex problems.

What are typical daily tasks and projects for someone in a quantitative modeling role?

In a Quantitative Modeling position, your daily activities usually include analyzing large datasets, building and validating predictive models, and developing algorithms to solve business or financial problems. You might spend time coding, running simulations, and interpreting model outputs to inform strategy or risk assessment. Collaboration is common—you'll often work with data scientists, business analysts, or subject matter experts to refine models and ensure they're aligned with organizational goals. The work is intellectually stimulating and fast-paced, with opportunities to see your analytical insights directly impact decision-making.

What are the key skills and qualifications needed to thrive in the quantitative modeling position, and why are they important?

To excel in Quantitative Modeling, a strong foundation in mathematics, statistics, and data analysis is essential, often complemented by a degree in a quantitative field such as mathematics, finance, engineering, or physics. Proficiency in programming languages like Python, R, MATLAB, or statistical software, as well as familiarity with data visualization tools and financial modeling certifications (such as CFA or FRM), is highly valued. Effective quantitative modelers possess strong problem-solving abilities, attention to detail, and the ability to communicate complex findings clearly to both technical and non-technical stakeholders. These skills enable accurate, data-driven decision-making and the creation of robust predictive models in business, finance, or technology sectors.

What does a quantitative modeler do?

A quantitative modeler develops mathematical and statistical models to analyze financial data, assess risk, and support decision-making. They use programming languages like Python or R and tools such as Excel or specialized software, often working in finance, investment, or risk management environments.

What are popular job titles related to Quantitative Modeling jobs in Berkeley, CA?

For Quantitative Modeling jobs in Berkeley, CA, the most frequently searched job titles are:

What cities near Berkeley, CA are hiring for Quantitative Modeling jobs?

Cities near Berkeley, CA with the most Quantitative Modeling job openings:

Infographic showing various Quantitative Modeling job openings in Berkeley, CA as of August 2026, with employment types broken down into 86% Full Time, 11% Part Time, and 3% Contract. Highlights an 83% Physical, 5% Hybrid, and 12% Remote job distribution, with an average salary of $208,187 per year, or $100.1 per hour.

Sr. Staff Quantitative Product Researcher

Pinterest

San Francisco, CA • On-site, Remote

Full-time

Posted 7 days ago


Job description

Pinterest is looking for a Sr. Staff Quantitative Product Researcher to lead the development and evolution of user-centered measurement across our consumer experience. As the volume of measurement asks grows, we need a seasoned researcher who can partner with Data Science and Engineering as an equal - not just contributing to metrics work, but guiding it end-to-end and shaping the direction of how we measure the Pinner experience.

In this role, you'll own the full arc of measurement work: identifying what we should be measuring, designing surveys that capture the constructs that matter, validating that our metrics are reliable and sensitive, guiding experimentation plans to prove they can move, and partnering with DS and Eng to build behavioral proxies or predictive models where they're needed. You'll also extend this work into how we evaluate and maintain the systems that depend on these metrics - informing when models need retraining, whether they generalize across user segments, and what levers actually move the outcomes we care about. You'll bring expertise in behavioral analysis, statistical modeling, survey methodology, and experimentation to strategic questions on the holistic Pinner experience, and you'll present findings to senior audiences and partner with leaders to turn learnings into strategy.

What you'll do:

  • Lead the development of user-centered metrics end-to-end: define the construct, design and validate the survey instrument, establish reliability and sensitivity, guide the experimentation plan to prove the metric can move, and partner with DS and Eng to build behavioral proxies or predictive models when appropriate
  • Extend measurement work into model stewardship - inform retraining decisions, evaluate generalizability across user segments, and stress-test where models do and don't hold up
  • Conduct deep-dive learning analyses to uncover the drivers and levers behind key metrics, and translate those into actionable direction for product and DS partners
  • Set and execute the learning agenda across a broad problem space - prioritize the questions that matter most, choose the right methods (surveys, behavioral analysis, quasi-experimental approaches, modeling), and work on the right project at the right time
  • Show up as an equal partner to Data Science and Engineering, shaping the direction of measurement work rather than executing against someone else's spec
  • Synthesize across behavioral analyses, experiment results, qualitative insights, and your own work to inform product and business decisions
  • Present to senior leadership and tailor socialization for those audiences
  • Partner with research managers to set quantitative research direction and mentor more junior quantitative researchers

What we're looking for:

  • 7+ years of quantitative user research experience with large-scale consumer data, including a track record of leading metric development end-to-end - from construct definition through survey validation, experimental validation, and behavioral proxy/predictive modeling
  • Deep expertise in survey methodology (construct validity, reliability, sensitivity), statistical modeling, experimentation at scale, and behavioral analysis
  • Experience informing ML model evaluation and maintenance - retraining triggers, generalizability across segments, and known failure modes
  • Fluency in R or Python and SQL, and strong data visualization skills
  • Demonstrated ability to operate as a peer to Data Science and Engineering - guiding the direction of technical work, not just contributing to it
  • Proactive - identifies the important questions and problems even when stakeholders aren't asking, and brings partners along
  • Experience working horizontally across teams, developing strategy with xfn partners, and presenting to senior leadership
  • Experience successfully leveraging AI tools in the research process with proper discernment and a high quality bar
  • PhD preferred in a computational social science (economics, sociology, psychology), statistics, computer science, or related field - or equivalent practical experience

Relocation Statement:

  • This position is not eligible for relocation assistance. Visit our PinFlex page to learn more about our working model. 

In-Office Requirement Statement:

  • We recognize that the ideal environment for work is situational and may differ across departments. What this looks like day-to-day can vary based on the needs of each organization or role.
  • This role will need to be in the office for in-person collaboration 1-2 times every 6-months and therefore can be situated anywhere in the country. 

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