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

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 ...

Shape the direction of some of our key data science areas - segmentation, recommendation systems, forecasting, product analytics, churn prediction and insights. * Work closely with Engineering ...

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

... 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 ...

... 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 ...

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

Figma is growing our Finance Data Science team at a pivotal moment in the company\'s evolution. As a public company, the accuracy, scalability, and sophistication of our financial data systems have ...

Data Engineer

San Francisco, CA · On-site +1

$145K/yr

This is a remote position. Duties * Support production systems and help triage issues during live ... Knowledge of data science and machine learning concepts * Professional working experience with MLB ...

Data Engineer

San Francisco, CA · On-site +1

$160K/yr

This is a remote position. Duties * Support production systems and help triage issues during live ... Knowledge of data science and machine learning concepts * A strong interest in sports and sports ...

Coordinate Experimental, Data Science, Data Engineering and AI Research teams to translate biological structure into learnable representations-defining priorities and appropriate structures for ...

Showing results 41-60

Remote Data Science information

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 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).

Can I work remotely as a remote data scientist?

Yes, many remote data scientist positions are available, allowing professionals to work from anywhere with a reliable internet connection. These roles often require skills in programming, data analysis, and familiarity with tools like Python, R, or SQL, and may involve collaboration through online platforms. Remote work arrangements are common in the data science field, especially with the increasing adoption of cloud-based tools and flexible schedules.

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.

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, 84% Full Time, 11% Part Time, and 4% Contract. Highlights an 87% Physical, 4% Hybrid, and 9% Remote job distribution.

Senior Data Scientist

Nash, Inc.

San Francisco, CA • On-site, Remote

Full-time

Medical, Dental, Vision, PTO

Posted 16 days ago


Job description

Senior Data Scientist
About Nash
Nash is the autonomic logistics platform. We unify decisioning and execution across fleets, carriers, providers, and fulfillment networks, continuously adapting as conditions change and pursuing the best possible outcome for each business.
The world's largest retailers, grocers, and pharmacies, including Walmart, 7-Eleven, Woolworths, and Coles, run critical logistics workflows on Nash. Your work will influence real-world decisions across millions of deliveries.
Nash was founded in 2021 by Mahmoud Ghulman and Aziz Alghunaim. We are backed by Y Combinator, a16z, OpenAI, and other leading investors, and headquartered in San Francisco.
About the role
We are hiring Nash's first Data Scientist. You will combine product judgment, logistics or marketplace expertise, and pragmatic machine learning skills to build data products from discovery through production and measurement.
You will work across pricing, dispatch, carrier selection, ETA prediction, routing, and supply-demand forecasting. This is a high-ownership role for someone who can find valuable problems, turn ambiguity into measurable outcomes, and build the models and systems needed to improve those outcomes in production.
You will partner directly with Product, Engineering, Operations, customers, and company leadership.
What you'll do
  • Identify and scope high-impact opportunities across pricing, cost prediction, dispatch, carrier selection, ETA prediction, routing, and marketplace balancing.
  • 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, geospatial data, carrier performance, customer constraints, and SLA outcomes.
  • Build models that account for real-world logistics constraints, shifting demand, provider availability, and service requirements.
  • Develop production data pipelines and model integrations using Python, SQL, and Snowflake.
  • Partner with engineers to serve models through APIs, batch pipelines, or real-time decision systems.
  • Establish evaluation frameworks, monitoring, experimentation, and A/B testing practices.
  • Measure model performance against business outcomes such as cost, reliability, on-time delivery, and operational intervention.
  • Work directly with enterprise customers to understand their operations and convert business requirements into technical approaches.
  • Communicate findings, tradeoffs, and recommendations clearly to technical and non-technical audiences.

What you'll bring
  • 4+ years of experience as a Data Scientist, Machine Learning Engineer, or in a related quantitative role.
  • Experience in logistics, marketplaces, supply chain, operations research, or another domain with complex real-world constraints.
  • A record of independently taking data science projects from problem definition through production and measurement.
  • Strong proficiency in Python and SQL, with experience working in cloud data warehouses. Snowflake experience is preferred.
  • Experience building and maintaining production machine learning systems. Deep MLOps specialization is not required.
  • Strong product judgment and the ability to connect modeling decisions to customer and business outcomes.
  • Comfort working with incomplete data, ambiguous questions, and changing operational conditions.
  • Clear written and verbal communication, including experience working with customers or senior stakeholders.
  • High agency in a fast-moving environment. You notice valuable problems and act on them.

Bonus
  • Experience with routing, ETA modeling, optimization algorithms, or geospatial data.
  • Familiarity with dispatch systems, carrier networks, logistics marketplaces, or pricing models.
  • Experience with supply-demand forecasting or marketplace balancing.
  • Exposure to dbt, Airflow, or related data orchestration tools.
  • Experience deploying models through APIs or real-time decision systems.
  • Prior experience at an early-stage company or in a founding data role.

Why this role matters
The decisions Nash makes affect what a delivery costs, which resource handles it, when it arrives, and whether the customer's promise holds when conditions change.
As our first Data Scientist, you will define how Nash uses operational data to make those decisions sharper. The models you build will move quickly from analysis into live logistics workflows, giving you a direct view into their customer and business impact.
What you'll love about Nash
  • An early-stage, well-funded company with real revenue and global enterprise customers
  • Significant ownership and autonomy, with direct collaboration with the founders
  • Quarterly team onsites to connect and align in person
  • Competitive compensation and meaningful equity
  • Flexible paid time off
  • Health, dental, and vision insurance

Equal opportunity
At Nash, we believe diverse teams are the strongest teams. We invite applicants of all genders, races, ethnicities, nationalities, ages, religions, sexual orientations, disability statuses, educational experiences, family situations, and socioeconomic backgrounds.
More about Nash
Nash is the platform that powers modern logistics.
Commerce has inverted. For decades, customers came to where products and services were. Now products and services come to them, on their terms, in real time. That shift has turned every company into a logistics company, even though almost none of them were built to be one. Couriers, fleets, gig workers, parcel carriers, in-store labor, and increasingly autonomous systems all have to be coordinated in real time, against tighter windows and rising expectations, with hard-fought customer trust on the line.
Nash unifies decisioning, execution, and capacity into a single programmable platform. Real-time, AI-native intelligence determines what should happen, operational control executes it, and the platform dynamically orchestrates capacity from any source: a company's own fleets, partners, or the Nash delivery network. Whether a job involves a courier, a gig driver, an internal fleet, a store employee, a technician, or an autonomous vehicle, Nash selects the right resource and manages execution through completion.
We power delivery and logistics for some of the most recognizable brands in commerce, including Walmart, Urban Outfitters, 7-Eleven, and Woolworths, alongside platforms like Shopify and Toast. Over the next decade, logistics will become as foundational to commerce as payments, cloud, and connectivity. Nash is the platform that powers it.
Nash was founded in 2021 by Mahmoud Ghulman (2x Founder, MIT) and Aziz Alghunaim (2x Founder, 2x YC, Ex-Palantir, MIT) and is backed by Y Combinator, a16z, and other top investors. We are headquartered in San Francisco.
What You'll Love About Us
• Early-stage, well-funded startup - directly impact the company and grow your career!
• Quarterly broader team on-sites to bond with teammates
• Competitive compensation and opportunity for equity
• Flexible paid time off
• Health, dental, and vision insurance