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

Head of Fraud Operations

Santa Ana, CA · On-site +1

$139K - $200K/yr

For remote roles, and at our discretion, candidates may be asked to participate in an on-site ... Data Science on models; and builds the team, tooling, SLAs, and metrics that hold fraud losses down ...

SDET, Remote opportunity

Irvine, CA · On-site +1

$130K - $145K/yr

Hybrid if local to Irvine, CA. 100% remote if you live more than 30 miles from the office. Our ... data management * Bachelor's degree in Computer Science, Engineering, or a related field, or ...

Showing results 21-40

Remote Data Science information

See Riverside, CA salary details

$23.7K

$105.5K

$201.3K

How much do remote data science jobs pay per year?

As of Aug 23, 2026, the average yearly pay for remote data science in Riverside, CA is $105,494.00, according to ZipRecruiter salary data. Most workers in this role earn between $54,493.00 and $146,323.00 per year, depending on experience, location, and employer.

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 Riverside, CA?

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

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

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

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

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

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

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

Infographic showing various Remote Data Science job openings in Riverside, CA as of August 2026, with employment types broken down into 1% As Needed, 83% Full Time, 13% Part Time, and 3% Contract. Highlights an 88% Physical, 3% Hybrid, and 9% Remote job distribution, with an average salary of $105,494 per year, or $50.7 per hour.

Senior Manager, Clinical Data Management

JENAVALVE TECHNOLOGY INC

Irvine, CA • Remote

Full-time

Re-posted 25 days ago


Job description

Job Title: Senior Manager, Clinical Data Management

Role Level: People Manager

Supervisor/Manager Title: Director, Biostatistics & Data Management

Job Location & Environment: Remote – Home Office

Job Description Summary: JenaValve Technology is building something meaningful — and this role is at the center of it. As the company brings clinical data management fully in-house for the first time, the Senior Manager, Clinical Data Management will own that function from the ground up: building team capability, establishing process infrastructure, and ensuring data integrity across JenaValve’s active interventional and registry trials. Reporting to the Director, Biostatistics & Data Management, this individual directly manages a team of five and works as a true partner to Clinical Operations, Field Monitoring, and Biostatistics to keep trial data clean, query-resolved, and submission-ready.

Job Responsibilities:

  • Lead and develop a team of five direct reports (two Specialists, Clinical Data Management and one Coordinator, Clinical Data Management, plus two existing team members); provide day-to-day direction, performance feedback, workload planning, and professional development to build a high-performing, scalable data management function.
  • Own the end-to-end data management program for all active clinical trials, including data cleaning operations, query lifecycle management, data review workflows, and data lock readiness; establish and enforce data quality standards across all studies in alignment with applicable regulations and internal SOPs.
  • Serve as the technical lead and JenaValve subject matter expert for EDC systems; partner with CRO vendors on EDC configuration, updates, and migrations; ensure Specialists are trained and equipped to serve as functional EDC experts and primary CRO coordination contacts for system-related activities.
  • Establish and maintain data management planning documents, data management plans (DMPs), and study-specific data conventions; oversee authorship and lifecycle management of data management SOPs and work instructions in coordination with Clinical Compliance.
  • Build and maintain a strong dotted-line partnership with Clinical Operations, CRAs, and Field Monitoring teams to ensure prompt protocol deviation identification, site data performance monitoring, and enrollment data accuracy; serve as the data management voice in cross-functional study team meetings.
  • Oversee vendor quality and performance for CRO data management activities during the transition to in-house operations; ensure continuity of data quality through the insourcing period and establish benchmarks for ongoing CRO performance where external support is retained.
  • Partner with Biostatistics on data standards (CDISC/CDASH), database lock procedures, and submission dataset readiness; ensure alignment between data management outputs and statistical analysis requirements.
  • Monitor regulatory developments relevant to clinical data management, including FDA guidance on electronic data capture, 21 CFR Part 11, and ICH E6(R3) data integrity expectations; evaluate impact on operations and procedures and recommend updates as appropriate.
  • Support PMA/IDE submission activities as they relate to data quality, data management documentation, and traceability of clinical data; complete assigned training for internal SOPs and maintain current knowledge of applicable regulations and guidance.
  • Develop, manage, and communicate data management timelines for study-level deliverables (e.g., interim analyses, data cleaning milestones, database locks, submission readiness); proactively identify risks to timelines and drive mitigation strategies across internal teams and external partners.
  • Lead data management readiness for internal and external audits and regulatory inspections; ensure documentation, system validation evidence, and data traceability meet inspection-readiness standards; serve as the data management point of contact during sponsor audits and CRO audits.

Required Education and Experience:

  • 7+ years of clinical data management experience in the pharmaceutical, biotechnology, or medical device industry; medical device or cardiovascular/structural heart experience strongly preferred.
  • Minimum 3 years in a lead or senior data management role with demonstrated ownership of study-level data cleaning, query management, and database lock activities.
  • Prior people management experience; ability to lead, develop, and retain direct reports in a growing, fast-paced environment.
  • Bachelor’s degree or higher in life sciences, health sciences, informatics, or a related field required; advanced degree preferred.
  • Thorough knowledge of ICH E6(R3), 21 CFR Parts 11 and 812, and CDISC/CDASH data standards; demonstrated experience authoring or overseeing data management plans and SOPs.
  • Experience managing or transitioning data management functions in-house from a CRO is a significant advantage.

Skills and Abilities Required for This Job:

  • Deep proficiency in EDC platforms (Medidata Rave, Oracle InForm, REDCap, or equivalent); experience overseeing EDC build review, UAT coordination, and system migration in partnership with CRO or vendor teams.
  • Strong analytical and problem-solving skills; ability to identify data quality trends, escalate risks, and implement corrective strategies across multiple concurrent studies.
  • Demonstrated ability to build collaborative partnerships with Clinical Operations, CRAs, Field Monitoring, and Biostatistics; proven cross-functional credibility in a clinical trial environment.
  • Excellent written and oral communication skills; able to produce clear data management documentation, status summaries, and executive-level updates; proficient in Microsoft Office Suite and eTMF/document management systems.

Physical Requirements:

  • Travel up to 15%, primarily for clinical team meetings, site visits, vendor engagements, and periodic home office visits.