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

Teleflora

Data Scientist, Modeler

Los Angeles, CA · On-site +1

The Data Scientist will also support A/B testing by validating results, while not owning test ... Python (preferred) or R * SQL / BigQuery (GCP ecosystem) * Work with modern AI tooling: * LLM APIs ...

GDIT

AI Data Scientist

Los Angeles, CA · On-site +1

Data Science and Data Engineering Job Qualifications: Skills: AI Systems, Big Data, Datasets ... a remote work model GDIT IS YOUR PLACE At GDIT, the mission is our purpose, and our people are at ...

TSMG

AI/ML Data Contributor

Los Angeles, CA · Remote

Participate in remote assignments or attend on-site sessions when required * Follow project ... Previous experience in data annotation, QA, or testing * Interest in AI, machine learning, or ...

TSMG

AI/ML Data Contributor

Los Angeles, CA · Remote

Participate in remote assignments or attend on-site sessions when required * Follow project ... Previous experience in data annotation, QA, or testing * Interest in AI, machine learning, or ...

Sparks Wiz Limited

Junior Data Analyst

Los Angeles, CA · On-site +1

$26 - $37/hr

Bachelors degree in Data Science, Statistics, Mathematics, Computer Science, Engineering, or a ... Skills: * Proficiency in data analysis tools and software (e.g., Excel, SQL, Python, R)

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All JobsData Scientist R JobsData Scientist R Remote JobsData Scientist R Remote Jobs in Los Angeles, CA

Data Scientist R Remote information

See Los Angeles, CA salary details

$40.4K

$132.3K

$211.7K

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

As of Aug 9, 2026, the average yearly pay for data scientist r remote 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 a data scientist R remote?

Data Scientist R Remote jobs are positions where professionals use the R programming language to analyze and interpret complex data, develop statistical models, and generate actionable insights, all while working outside of a traditional office setting. These roles often involve collaborating with teams virtually, cleaning and preparing data, and building predictive models using R and related tools. Remote data scientists leverage cloud-based platforms and communication tools to work effectively from any location. The role typically requires strong analytical skills, proficiency in R, and experience with data visualization and machine learning techniques.

How does a remote data scientist specializing in R typically collaborate with cross-functional teams?

As a remote Data Scientist with expertise in R, collaboration with cross-functional teams—such as product managers, engineers, and business analysts—is commonly facilitated through virtual meetings, shared documentation, and version control systems like Git. You'll often participate in sprint planning, present data-driven insights, and contribute to collaborative code reviews. Effective communication and proactive sharing of progress or challenges are key to ensuring alignment, especially when working across time zones. Utilizing tools like Slack, Jira, and cloud-based notebooks further streamlines teamwork and maintains project momentum.

What are the key skills and qualifications needed to thrive as a data scientist R remote?

To thrive as a Data Scientist (R, Remote), you need strong analytical skills, statistical knowledge, and a background in mathematics or computer science, often supported by a relevant degree. Proficiency in R programming, data visualization tools, and familiarity with machine learning libraries are typically required, and certifications like the Microsoft Certified: Azure Data Scientist Associate can be advantageous. Excellent problem-solving abilities, effective communication, and self-motivation are critical soft skills for collaborating remotely and translating data insights into actionable business decisions. These skills enable you to derive meaningful insights from complex data sets, drive data-driven strategies, and work efficiently in a remote team environment.

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

AspectData Scientist R RemoteData Analyst R Remote
Required CredentialsBachelor's or Master's in Data Science, Statistics, or related field; proficiency in RBachelor's in Statistics, Mathematics, or related field; proficiency in R
Work EnvironmentRemote, collaborative teams, project-basedRemote, reporting to managers, data reporting tasks
Employer & Industry UsageTech, finance, healthcare, consultingRetail, marketing, finance, healthcare
Common Search & ComparisonYesYes

Data Scientist R Remote and Data Analyst R Remote roles share similar skills in R programming and remote work environments. However, Data Scientists typically handle complex modeling, machine learning, and predictive analytics, requiring advanced statistical knowledge. Data Analysts focus on data reporting, visualization, and descriptive analysis. Both roles are vital across industries, but Data Scientists often require higher-level credentials and experience.

What are popular job titles related to Data Scientist R Remote jobs in Los Angeles, CA? For Data Scientist R Remote jobs in Los Angeles, CA, the most frequently searched job titles are:
What job categories do people searching Data Scientist R Remote jobs in Los Angeles, CA look for? The top searched job categories for Data Scientist R Remote jobs in Los Angeles, CA are:
What cities near Los Angeles, CA are hiring for Data Scientist R Remote jobs? Cities near Los Angeles, CA with the most Data Scientist R Remote job openings:
Data Scientist R Remote jobs near you

Real Estate Data Scientist - Remote

Harbor Freight Tools

Calabasas, CA • On-site, Remote

$98K - $147K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 14 days ago

Job description

The Real Estate Data Scientist is responsible for developing advanced analytical models and data-driven tools that support strategic real estate decisions across the organization. This role partners closely with Real Estate, Finance, Marketing, and Supply Chain teams to deliver predictive insights related to site selection, network optimization, sales forecasting, and market planning. This role incorporates advanced spatial modeling, geostatistics, and geospatial data engineering to evaluate trade areas, quantify market potential, and optimize network performance.
This position combines strong statistical modeling, data engineering, and business acumen to translate complex data into actionable recommendations. The Real Estate Data Scientist plays a critical role in advancing the organization's use of machine learning, automation, and predictive analytics to improve decision quality and scalability. This is a senior individual contributor role with no direct people management responsibility.
Duties and Responsibilities
  • Advanced Analytics & Predictive Modeling
    • Develop and deploy predictive models for site selection, sales forecasting, cannibalization, and market potential.
    • Build and maintain machine learning models using regression, classification, clustering, optimization, and spatial modeling techniques.
    • Apply spatial statistical methods (e.g., spatial regression, geographically weighted regression, spatial autocorrelation) to capture geographic variation in demand drivers.
    • Develop trade area and customer draw models (e.g., Huff/gravity models) to estimate market share and competitive impact.
    • Incorporate spatial features such as proximity, co-tenancy, demographics, traffic patterns, and nearby store performance into predictive models.
    • Design methodologies for forecasting store performance under various scenarios, including spatial and competitive effects.
    • Continuously monitor and improve model performance and accuracy. 
  • Data Engineering & Automation
    • Design scalable data pipelines integrating real estate, customer, demographic, sales, and geospatial datasets (parcel, census, traffic, mobility, POI data).
    • Perform geospatial data processing including geocoding, spatial joins, coordinate transformations, and spatial indexing (e.g., H3 or similar frameworks).
    • Write efficient SQL and Python workflows to automate recurring analyses, spatial feature engineering, and model refreshes.
    • Ensure data quality, consistency, and reproducibility across analytical outputs, including alignment of spatial boundaries and geographic hierarchies.
  • Real Estate Strategy & Decision Support
    • Partner with Real Estate teams to support site selection, market entry, relocations, and closures.
    • Develop drive-time and network-based trade area analyses to assess accessibility and market reach.
    • Conduct market coverage and white space analysis to identify expansion opportunities and underserved areas.
    • Build location-allocation and network optimization models to determine optimal site placement.
    • Quantify cannibalization and competitive effects using spatial overlap and proximity-based modeling.
    • Provide quantitative insights for Real Estate Committee (REC) evaluations and executive decisions.
    • Develop scoring frameworks and decision tools to prioritize opportunities.         
  • Visualization & Communication
    • Create clear, compelling visualizations and dashboards (Tableau, Power BI, or similar) to communicate insights.
    • Develop interactive geospatial visualizations including trade area maps, performance heatmaps, and market opportunity analyses.
    • Present analytical findings and recommendations to senior leadership and non-technical stakeholders.
  • Experimentation & Innovation
    • Design and execute experiments (A/B tests, quasi-experimental designs) to evaluate real estate strategies.
    • Implement geo-based testing frameworks (e.g., test vs. control markets) to measure impact of site decisions.
    • Apply causal inference methods (e.g., difference-in-differences, synthetic control) accounting for geographic spillovers.
    • Explore new data sources (e.g., mobility, foot traffic) and modeling techniques to enhance predictive capabilities.
    • Contribute to building a best-in-class real estate analytics capability.
  • Cross-Functional Collaboration
    • Work closely with GIS, Data Engineering, Finance, Marketing, and IT teams to align data and models.
    • Partner with GIS teams to ensure alignment between spatial analysis, mapping, and production data pipelines.
    • Translate business problems into analytical solutions and actionable insights.
Scope
  • Staff supervision and development:  No
  • Decision making: 
    • Develops models and analytical frameworks used in strategic decision-making
  • Travel:  Up to 10%
  • Flex Designation:  Anywhere

The anticipated salary range for this position is $98,500-$147,800 depending on location, knowledge, skills, education and experience. This position is also eligible for an annual discretionary bonus. In addition, we offer comprehensive and competitive benefits to Associates (and their families) such as medical, dental, vision, life insurance, short-term and long-term disability. Eligible Associates are able to enroll in our company's 401k plan. Associates will accrue paid time off up to 236 hours per year (inclusive of PTO, floating holidays, and paid holidays). Paid sick time up to 80 hours per year unless otherwise required by law.

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