ZipRecruiter

Log In

2

Remote Data Analyst Jobs in San Ramon, CA (NOW HIRING)

Argyle Infotech

Senior Business Data Analyst

San Francisco, CA · Remote

$101.30K - $127.80K/yr

Senior Business Data Analyst The Customer Success (CS) Data and Analytics team has an exciting opportunity to tackle some of the hardest problems in developing a virtual expert platform using ...

Midi Health

Senior Data Analyst, Commerce

Palo Alto, CA · On-site +1

$101.10K - $127.50K/yr

Director Data Science + Analytics About Midi Health: Midi Health is the fastest-growing virtual clinic focused exclusively on women's midlife health. We deliver insurance-covered care for women ...

next page

Showing results 1-20

People also search for

All JobsRemote Data Analyst JobsRemote Data Analyst Jobs in San Ramon, CA

Remote Data Analyst information

See San Ramon, CA salary details

$38K

$92.4K

$152K

How much do remote data analyst jobs pay per year?

As of May 28, 2026, the average yearly pay for remote data analyst in San Ramon, CA is $92,352.00, according to ZipRecruiter salary data. Most workers in this role earn between $69,800.00 and $108,400.00 per year, depending on experience, location, and employer.

What Does a Remote Data Analyst Do?

Remote data analysts use a range of methods to chart, examine, and analyze data for their clients. Unlike in-house data analysts, remote data analysts, work from home or a different location outside of the office. As a remote data analyst, your job is to evaluate a company’s data using a combination of mathematical inspection, transformation, and modeling techniques to simplify and condense it. Once the analysis is complete, you create reports for management to use to make critical decisions; this is why remote data analysts need to confirm the accuracy of the data. You may also need to present your reports to stakeholders.

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

To thrive as a Remote Data Analyst, you need strong analytical skills, proficiency in statistics, and a degree in a quantitative field such as mathematics, statistics, or computer science. Familiarity with data analysis tools like SQL, Excel, Python or R, and visualization platforms such as Tableau or Power BI is typically required. Excellent communication, self-motivation, and time management are crucial soft skills for collaborating remotely and presenting insights effectively. These skills ensure accurate data-driven decision-making and effective remote teamwork in a digital work environment.

How do Remote Data Analysts typically collaborate with team members and stakeholders given the virtual work environment?

Remote Data Analysts often rely on digital communication tools such as Slack, Microsoft Teams, and Zoom to stay connected with colleagues and stakeholders. They participate in regular virtual meetings, share dashboards or reports via cloud-based platforms, and provide data-driven insights to support decision-making. Successful remote analysts proactively communicate their findings, clarify requirements, and coordinate with cross-functional teams such as IT, marketing, or finance to ensure alignment on project goals and deliverables.

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

AspectRemote Data AnalystRemote Data Scientist
Required CredentialsBachelor's in Data, Statistics, or related field; often certifications in Excel, SQL, or TableauBachelor's or Master's in Data Science, Computer Science, or related; certifications in Python, R, machine learning
Work EnvironmentPrimarily office-based or remote, focusing on data analysis and reportingPrimarily remote, involving complex data modeling and predictive analytics
Employer & Industry UsageUsed across finance, marketing, healthcare, and retail sectorsCommon in tech, finance, and research industries

Remote Data Analysts focus on interpreting data, creating reports, and supporting decision-making, while Remote Data Scientists develop models, perform advanced analytics, and work on predictive insights. Both roles require strong analytical skills, but Data Scientists typically have more technical expertise in programming and machine learning.

More about Remote Data Analyst jobs
What are the most commonly searched types of Data Analyst jobs in San Ramon, CA? The most popular types of Data Analyst jobs in San Ramon, CA are:
What are popular job titles related to Remote Data Analyst jobs in San Ramon, CA? For Remote Data Analyst jobs in San Ramon, CA, the most frequently searched job titles are:
What job categories do people searching Remote Data Analyst jobs in San Ramon, CA look for? The top searched job categories for Remote Data Analyst jobs in San Ramon, CA are:
What cities near San Ramon, CA are hiring for Remote Data Analyst jobs? Cities near San Ramon, CA with the most Remote Data Analyst job openings:
Remote Data Analyst jobs near you
Infographic showing various Remote Data Analyst job openings in San Ramon, CA as of May 2026, with employment types broken down into 86% Full Time, 6% Part Time, and 8% Contract. Highlights an 21% Physical, 9% Hybrid, and 70% Remote job distribution, with an average salary of $92,352 per year, or $44.4 per hour.

Senior Business Data Analyst

Argyle Infotech

San Francisco, CA • Remote

$101.30K - $127.80K/yr

Other

This job post has expired today. Applications are no longer accepted.

Job description

Senior Business Data Analyst

The Customer Success (CS) Data and Analytics team has an exciting opportunity to tackle some of the hardest problems in developing a virtual expert platform using analytics. We are seeking a seasoned Senior Business Data Analyst who is a data-driven individual with excellent analytical skills, an agile mindset, and a passion for delivering high impact insights. We are building the analytics that drive the platform we use to onboard, manage and utilize our tax and accounting professionals. This role will partner closely with several Product managers and Operations managers to produce analytics, insights, and reporting to support these needs. This role is expected to understand the business and draw from that knowledge to produce data-driven output to help multiple organizations leverage a powerful expert platform for customer success.

5-8+ years of experience working with data and analytics with knowledge of statistics

Highly proficient in SQL, Data Visualization software (Qliksense, Tableau, Amplitude), and Excel

Excellent problem-solving and logic skills and end-to-end quantitative thinking

Ability to manage multiple projects simultaneously to meet objectives and key deadlines

Outstanding communications skills with both technical and non-technical colleagues

Strong ability to tell stories with data, educate effectively, and instill confidence, motivating stakeholders to act on recommendations

Proactive and inquisitive learner who seeks out and capitalizes on opportunities for change that enhance the business, rather than reacting to circumstances

Strong organization, time management and task prioritization skills

Ability to adapt and flex given changing environments and priorities

Experience in a scripting language to automate and reuse code. Optional but encouraged: experience in prompt engineering to accelerate development tasks

Experience in defining metrics and instrumenting data tracking

Partner with Product and Operations leaders and other analytics teams to enable data driven decisions and key customer insights in the management and operation of our expert network.

Collaborate across product management and engineering to ensure reporting solutions are scalable, repeatable, effective, and meet expectations for a variety of stakeholders.

Define, implement, and standardize metrics, reports and dashboards leveraging state of the art business intelligence tools.

Provide recommendations utilizing statistical model generation using multiple types of data, business knowledge, programmatic insights, and strategic assumptions when data doesn’t exist.

Suggest ad-hoc analytic questions, contribute to decision making through opportunity sizing, and facilitate use of self-serve standard reports.

Establish data quality standards, troubleshoot data validation, proactively identify issues, and see them to resolution.

Apply