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Remote Data Science Jobs in Berkeley, CA (NOW HIRING)

This is full-time remote position. Key Responsibilities * Develop, deploy and monitor predictive ... Maintain a pulse on the current state of data science and basketball analytics * Other duties as ...

The Data Science TeamOur Impact Data is core to Parafin's mission to grow small businesses. Our platform partnerships and portfolio provide rich insight into SMB financial health, allowing us to ...

The Data Science group is made up of people from a diverse set of backgrounds and perspectives, trained in fields as wide-ranging as economics, psychology, geography, physics, statistics, and ...

Data Scientist

San Francisco, CA · On-site +1

$160K - $200K/yr

This is a remote position, but we do have an office in San Fransisco. You will be the first data scientist on the team working through and building models from scratch that will be pivotal for our ...

Data Scientist

San Francisco, CA · Remote

$160K - $200K/yr

This is a remote position, but we do have an office in San Fransisco. You will be the first data scientist on the team working through and building models from scratch that will be pivotal for our ...

We leverage massive data and cutting-edge science to automate and optimize TV advertising to drive ... Visit our PinFlex page to learn more about our working model. #LI-SM4 #LI-REMOTE At Pinterest we ...

Advanced degree (Master's with 2+ years experience or equivalent) in data science, bioinformatics ... Additionally, for remote roles open to individuals in unincorporated Los Angeles - including remote ...

... of data science experience with demonstrable impact on business-critical forecasting and ... Employees approved for remote work must perform their duties from a single, company-approved based ...

Own data science initiatives from 0→1 discovery through 1→10 iteration, deployment, and performance improvement. * Work with large, messy operational datasets, including delivery events ...

Data Scientist

Berkeley, CA · On-site +1

$150K - $190K/yr

Bachelor's degree in a quantitative discipline (statistics, biostatistics, data science, computer science, or a related field) Preferred Qualifications * Master's degree in a quantitative discipline

Our Impact Data science is integral to Parafin's mission. Our platform partnerships and lending history provide rich insights into the financial health of small businesses around the world. This ...

... science, data engineering, or applied data role, ideally with exposure to messy, real-world or ... moving, remote environment with ambiguous, evolving priorities Salary Range: Salary ranges are ...

Showing results 21-40

Remote Data Science information

What is remote data science?

Remote data science refers to the practice of performing data analysis, modeling, and interpretation tasks from a location outside of a traditional office, such as from home or a co-working space. Remote data scientists use tools like Python, R, and SQL to analyze data, build predictive models, and communicate insights to stakeholders, all while collaborating virtually with their teams. This setup offers flexibility and can increase access to global job opportunities, but also requires strong self-motivation and communication skills to be effective.

What are the qualifications to get a remote data science job?

The qualifications for a remote data scientist depend in large part on your employer and their industry. Most employers expect remote data science professionals to have at least a bachelor’s degree in statistics, math, computer science, or a related field. Some expect postgraduate degrees in a field like data mining or machine learning or demonstrable skills in these areas. As a remote worker, you need access to relevant programs and an internet connection. You may also want to pursue certification, such as becoming a Certified Analytics Professional (CAP).

What are the key skills and qualifications needed to thrive as a remote data scientist, and why are they important?

To thrive as a Remote Data Scientist, you need strong analytical skills, proficiency in statistics, and a solid background in mathematics or computer science, often supported by a relevant degree. Expertise in programming languages such as Python or R, familiarity with machine learning libraries, and experience with cloud-based data platforms are typically required. Excellent communication, self-motivation, and time management skills help you effectively collaborate and deliver results in a remote environment. These skills ensure accurate data analysis, meaningful insights, and successful teamwork despite physical distance.

How do remote data scientists typically collaborate with cross-functional teams to deliver insights?

Remote data scientists often work closely with product managers, engineers, and business analysts using digital collaboration tools such as Slack, Zoom, and project management platforms. Regular virtual meetings, code sharing via Git repositories, and clear documentation are essential to ensure alignment and transparency. While working remotely can present challenges in communication, proactive updates and scheduled syncs help foster strong teamwork and keep projects on track.

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

AspectRemote Data ScienceRemote Data Analyst
Required CredentialsDegree in Data Science, Statistics, or related field; programming skills in Python/R; knowledge of machine learningDegree in Statistics, Mathematics, or related field; proficiency in Excel, SQL, and data visualization tools
Work EnvironmentCollaborative teams, research-focused, often involves building models and algorithmsData reporting, visualization, and interpreting data trends for decision-making
Employer & Industry UsageTech companies, finance, healthcare, e-commerceMarketing agencies, retail, finance, healthcare

Remote Data Science involves developing predictive models and advanced analytics, requiring programming and machine learning skills. Remote Data Analysts focus on interpreting data, creating reports, and visualizations. While both roles analyze data remotely, Data Scientists typically handle more complex modeling tasks, whereas Data Analysts focus on data interpretation and reporting.

Can I work remotely as a data scientist?

Yes, many data scientist roles are available as remote positions, especially in companies that prioritize flexible work arrangements. Remote data scientists typically need strong skills in programming, data analysis, and tools like Python or R, and may require familiarity with cloud platforms and collaboration tools. Availability depends on the employer's policies and the specific job requirements.

What are the most commonly searched types of Data Science jobs in Berkeley, CA?

The most popular types of Data Science jobs in Berkeley, CA are:

What are popular job titles related to Remote Data Science jobs in Berkeley, CA?

For Remote Data Science jobs in Berkeley, CA, the most frequently searched job titles are:

What job categories do people searching Remote Data Science jobs in Berkeley, CA look for?

The top searched job categories for Remote Data Science jobs in Berkeley, CA are:

What cities near Berkeley, CA are hiring for Remote Data Science jobs?

Cities near Berkeley, CA with the most Remote Data Science job openings:

Infographic showing various Remote Data Science job openings in Berkeley, CA as of August 2026, with employment types broken down into 1% As Needed, 80% Full Time, 17% Part Time, and 2% Contract. Highlights an 86% Physical, 3% Hybrid, and 11% Remote job distribution.

Staff Product Data Scientist, Lending

Block

San Francisco, CA • On-site, Remote

Full-time

Re-posted 15 days ago


Block rating

7.9

Company rating: 7.9 out of 10

Based on 16 frontline employees who took The Breakroom Quiz

9th of 21 rated payment service providers


Job description

It all started with an idea at Block in 2013. Initially built to take the pain out of peer-to-peer payments, Cash App has gone from a simple product with a single purpose to a dynamic ecosystem, developing unique financial products, including Afterpay/Clearpay, to provide a better way to send, spend, invest, borrow and save to our 50+ million monthly active customers. We want to redefine the world's relationship with money to make it more relatable, instantly available, and universally accessible.
Today, Cash App has thousands of employees working globally across office and remote locations, with a culture geared toward innovation, collaboration and impact. We've been a distributed team since day one, and many of our roles can be done remotely from the countries where Cash App operates. No matter the location, we tailor our experience to ensure our employees are creative, productive, and happy.

The Role

The Data Science team at Block turns unique customer and product data into decisions that expand access to financial services. Our Lending team powers decisioning behind Cash App Borrow, Afterpay, Square Loans, and the next generation of first-party credit products.

We're looking for a Product Data Scientist to help build, measure, and improve credit products that serve customers traditional credit systems often miss. You'll partner closely with product, engineering, and risk teams to define metrics, evaluate experiments, understand customer behavior, and turn ambiguous product questions into clear decisions.

This is an agentic data science role. You'll use AI tools and agent workflows to move faster and think more rigorously across the full data science loop: exploring messy datasets, building pipelines, stress-testing hypotheses, evaluating product changes, and turning analysis into decisions.

You Will
  • Turn complex product, customer, and risk data into clear insights, decision frameworks, and durable measurement systems for product, risk, and business partners
  • Use AI tools and agent workflows to improve both the speed and quality of analytical work, from accelerating exploration and automating repetitive tasks to generating hypotheses and stress-testing conclusions
  • Own end-to-end execution across analysis, metrics definition, experimentation, forecasting, visualization, and decision support
  • Define and maintain measurement frameworks for credit products, including customer eligibility, repayment behavior, product usage, loss performance, funnel health, and long-term customer outcomes
  • Partner with risk teams to evaluate model and policy performance, monitor cohorts, identify bias or drift, and connect risk decisions to product and business impact
  • Design and analyze experiments, rollouts, and policy changes that shape customer access, repayment outcomes, and product growth
  • Approach ambiguous product and risk questions from first principles, using statistical judgment to define the right cohorts, metrics, and decision criteria
  • Communicate insights clearly to technical, product, and business stakeholders, including risk partners and senior decision-makers
  • Lead technical direction and standards for the Block Data Science team - making and building consensus on key technical decisions, and creating reusable frameworks, measurement templates, and scalable tooling that remove complexity for others.
  • Drive localized cross-team impact by connecting measurement and insights across Lending products (Borrow, Afterpay, Square Loans) and partnering with senior stakeholders in product, engineering, and risk to align Data Science work with broader strategy.
  • Mentor and grow the team by developing junior data scientists, fostering a culture of analytical rigor and psychological safety, and contributing to hiring through interviews and calibrations
You Have
  • A bachelor's degree in statistics, data science, economics, computer science, or a similar quantitative field with 12+ years of experience in a relevant role OR
  • A graduate degree in statistics, data science, economics, computer science, or a similar quantitative field with 6-8+ years of experience in a relevant role
  • Advanced proficiency with SQL and experience building clear, decision-oriented data visualizations
  • Strong product, analytical, and statistical judgment, including the ability to turn ambiguous product, customer, or risk questions into sound analyses, communicate tradeoffs clearly, and support decisions
  • Experience using AI tools to improve the speed, quality, and durability of analytical work

What Block employees say

Pay

Hours and flexibility

Workplace

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