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Remote Data Science R Jobs in Los Angeles, CA (NOW HIRING)

Experian

Senior Data Modeling Analyst - Remote

Costa Mesa, CA · On-site +1

$92K - $116K/yr

Bachelor's degree in Computer Science, Data Science, Mathematics, Statistics, or a related ... Knowledge of statistical models and practical experience in predictive model development (Python, R ...

Sedgwick

Data Engineer AI

Los Angeles, CA · On-site +1

$123K - $148K/yr

You will be responsible for the "heavy lifting" required to fuel Data Science models and AI ... LI-TS1 #remote Sedgwickis an Equal Opportunity Employer and a Drug-Free Workplace. If you're ...

York Risk Services

Data Engineer AI

Los Angeles, CA · On-site +1

$123K - $148K/yr

You will be responsible for the "heavy lifting" required to fuel Data Science models and AI ... LI-TS1 #remote Sedgwickis an Equal Opportunity Employer and a Drug-Free Workplace. If you're ...

Relativity

Senior Applied Scientist

Los Angeles, CA · On-site +1

Posting Type Remote/Hybrid Job Overview WHO WE ARE Relativity is a leading legal data intelligence ... Applied Science Team The Applied Science team operates at the core of Relativity's AI development.

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All JobsRemote Data Science R JobsRemote Data Science R Jobs in Los Angeles, CA

Remote Data Science R information

See Los Angeles, CA salary details

$40.4K

$132.3K

$211.7K

How much do remote data science r jobs pay per year?

As of Jun 16, 2026, the average yearly pay for remote data science r in Los Angeles, CA is $132,252.00, according to ZipRecruiter salary data. Most workers in this role earn between $106,100.00 and $146,500.00 per year, depending on experience, location, and employer.

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

AspectRemote Data Science RRemote Data Analyst
Required SkillsStatistical analysis, R programming, data modeling, machine learningData visualization, basic statistical analysis, Excel, SQL
CertificationsR certifications, data science certificates, possibly advanced degreesData analysis certifications, Excel, SQL courses
Work EnvironmentCollaborative teams, research projects, data science platformsReporting, dashboards, business insights
Industry UsageTech, finance, healthcare, research institutionsMarketing, retail, finance, operations

Remote Data Science R roles focus on advanced statistical modeling and machine learning using R, often requiring specialized certifications and working on complex data projects. Remote Data Analysts typically handle data reporting, visualization, and basic analysis to support business decisions. While both roles involve data handling, Data Science R positions demand deeper technical expertise and programming skills.

What are Remote Data Science R jobs?

Remote Data Science R jobs are positions that involve using the R programming language to analyze and interpret data, build statistical models, and generate insights, all while working from a remote location. These roles typically require strong skills in data manipulation, visualization, and statistical analysis using R. Professionals in these positions may work for companies in various industries, collaborating with teams online and leveraging cloud-based tools. Remote Data Science R jobs offer flexibility, allowing individuals to work from home or anywhere with a reliable internet connection.

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, expertise in statistics, programming (Python or R), and typically a degree in data science, computer science, or a related field. Familiarity with data analysis tools, machine learning frameworks (like TensorFlow or scikit-learn), and cloud platforms (such as AWS or Google Cloud) is commonly required. Outstanding problem-solving, self-motivation, and effective virtual communication skills help you excel in remote environments. These abilities are essential for deriving actionable insights from data and collaborating efficiently across distributed teams.

How do remote Data Science R professionals typically collaborate with cross-functional teams while working from different locations?

Remote Data Science R professionals often use a combination of communication platforms (like Slack, Microsoft Teams, or Zoom) and project management tools (such as Jira or Trello) to stay connected with colleagues in engineering, product management, and business analysis. Sharing code and models through version control systems (like Git) and documenting workflows in shared repositories helps maintain transparency and collaboration. Regular virtual meetings and presentations are crucial for aligning goals, discussing progress, and receiving feedback. This collaborative approach ensures that data-driven insights effectively support organizational objectives, even in a distributed work environment.
What are the most commonly searched types of Data Science R jobs in Los Angeles, CA? The most popular types of Data Science R jobs in Los Angeles, CA are:
What are popular job titles related to Remote Data Science R jobs in Los Angeles, CA? For Remote Data Science R jobs in Los Angeles, CA, the most frequently searched job titles are:
What job categories do people searching Remote Data Science R jobs in Los Angeles, CA look for? The top searched job categories for Remote Data Science R jobs in Los Angeles, CA are:
What cities near Los Angeles, CA are hiring for Remote Data Science R jobs? Cities near Los Angeles, CA with the most Remote Data Science R job openings:
Remote Data Science R jobs near you

Senior Data Modeling Analyst - Remote

Experian

Costa Mesa, CA • On-site, Remote

$92K - $116K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted yesterday

Job description

Company Description

Experian is a global data and technology company, powering opportunities for people and businesses around the world. We operate across a range of markets, from financial services to healthcare, automotive, agribusiness, insurance, and many more. Experian invests in people and new advanced technologies to unlock the power of data. We have an amazing team of 25,200 people in 32 countries.

Job Description

You'll have opportunity to:

  • Independently deliver analytical projects across the consumer credit lifecycle, including acquisition, account management and collections
  • Build statistical and machine learning models through all phases of development, from design through training, evaluation, validation and implementation
  • Use a broad set of technologies: SQL, PySpark, Python, AWS and more to obtain insights from large volumes of data
  • Design and improve acquisition strategies, including segmentation, decision rules, and cut-off strategies
  • Translate findings into applicable business recommendations for partners
  • Collaborate with internal and external clients to determine the appropriate analysis parameters and performance measures to be applied, as well as requirements for decision tool and strategy implementation and monitoring.
  • Interpret results of analyses, identify trends and issues and recommend alternatives to support our goals.
  • Communicate with and deliver presentations to end-users on analysis results.
  • Produce implementation plans and participate in audits to help implement statistical models and other decision tools.
  • Help develop analytic and data products and services, and the enhancement of current processes and offerings.
Qualifications
  • Bachelor's degree in Computer Science, Data Science, Mathematics, Statistics, or a related quantitative field
  • 8+ years' experience with statistical and quantitative analysis, Machine Learning, Statistical Modeling including large-scale data manipulation in Credit Lending industry
  • Proficiency in Python (required) and SQL, with experience building scalable pipelines
  • Knowledge of statistical models and practical experience in predictive model development (Python, R, SAS).
  • Domain experience in financial services, with exposure to credit lending, credit risk modeling, and credit decisioning lifecycle (e.g., origination, underwriting, limit setting, portfolio monitoring)
  • Experience with model deployment and productionization, including CI/CD pipelines, version control, and integration of models into scalable, real-time or batch decisioning systems
  • Experience joining large datasets from multiple data sources, creating complex logic for data cleaning, outlier detecting, and refining business rules to validate and monitor the model forecast
  • Experience solving complex and unique problems
Additional Information

Our uniqueness is that we celebrate yours. Experian's people first, inclusive and purpose driven culture is multi award-winning; World's Best Workplaces 2025 (Fortune Global Top 25), Great Place To Work in 26 countries to name a few. Check out Experian Life on social or explore our Careers Site to understand why.

Our compensation reflects the cost of labor across several U.S. geographic markets. The base pay range for this position is listed above. Within this range, individual pay is determined by work location and additional factors such as job-related skills, experience, and education. You will be also eligible for a variable pay opportunity.

Experian is proud to be an Equal Opportunity Employer for all groups protected under applicable federal, state and local law, including protected veterans and individuals with disabilities. If you have a disability or special need that requires accommodation, please let us know at the earliest opportunity.

Benefits/Perks:

  • Great compensation package and bonus plan
  • Core benefits including medical, dental, vision, and matching 401K
  • Flexible work environment, ability to work remote, hybrid or in-office
  • Flexible time off including volunteer time off, vacation, sick and 12-paid holidays
  • Explore all our exciting benefits here: https://myexperianbenefits.com/

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