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Entry Level Data Analyst R Programming Jobs in Los Angeles, CA

Title- Data Analyst/BI Engineer Location- El Segundo, CA- Hybrid (3 days/week on-site) F2F INTERVIEW Type- Contract- C2C Works Duration- 12+ Months - Key Responsibilities Analyze and integrate data ...

Data Analyst / CDP Developer Location: Torrance, CA Duration: 6 Months JOB RESPONSIBILITIES Data Analysis and Development * Analyze customer data, event, and large-scale datasets to generate insights ...

Bachelor's degree in a sciences or engineering discipline or similar field or an equivalent combination of education plus work experience. 1+ years of experience in data analysis, preferably in a ...

Data Analyst

Downey, CA ยท On-site

Analyze data from various sources, using spreadsheets and smart sheets, to identify trends ... Bachelor's degree in Business Administration, Finance, Engineering, or any other related field.

Data Analyst

Irvine, CA ยท On-site

Analyze data from various sources, using spreadsheets and smart sheets, to identify trends ... Bachelor's degree in Business Administration, Finance, Engineering, or any other related field.

Software Engineer I, Data Science (New Grad)

Long Beach, CA ยท On-site

$120K - $144K/yr

Pre-launch, you'll analyze manufacturing telemetry, test logs, failure reports, and supplier data ... This is entry-level data science work supporting hardware production and spacecraft operations. You ...

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Entry Level Data Analyst R Programming information

See Los Angeles, CA salary details

$14

$35

$66

How much do entry level data analyst r programming jobs pay per hour?

As of Sep 14, 2026, the average hourly pay for entry level data analyst r programming in Los Angeles, CA is $35.48, according to ZipRecruiter salary data. Most workers in this role earn between $22.79 and $39.62 per hour, depending on experience, location, and employer.

What is an entry level data analyst r programming?

An Entry Level Data Analyst (R Programming) is a professional who uses the R programming language to collect, process, and analyze data to help organizations make informed decisions. They typically work with large datasets, create visualizations, and generate reports under the guidance of more experienced analysts. Entry-level data analysts are often responsible for basic data cleaning, statistical analysis, and supporting team projects while they develop their skills in R and data analysis techniques.

What skills and qualifications are needed to thrive as an entry level data analyst r programming?

To thrive as an Entry Level Data Analyst specializing in R Programming, you need a solid grounding in statistics, data cleaning, and analytical methods, typically supported by a relevant degree such as statistics, mathematics, or computer science. Proficiency in R programming, familiarity with data visualization tools (e.g., ggplot2), and experience with spreadsheet software or SQL are commonly required. Strong attention to detail, problem-solving abilities, and clear communication skills set outstanding candidates apart in this role. These skills are crucial to accurately interpret data, deliver actionable insights, and effectively collaborate with teams to support data-driven decision-making.

What are some typical challenges entry level data analysts face when working with R programming in a team setting?

Entry-level data analysts using R often encounter challenges such as adapting to existing codebases, understanding team-specific data workflows, and ensuring code reproducibility and documentation for collaborative projects. New analysts may also need to quickly learn version control practices (like using Git) and follow standardized procedures for data cleaning and reporting. Regular communication with senior analysts and participation in code reviews are essential to build both technical proficiency and teamwork skills.

What is the difference between Entry Level Data Analyst R Programming vs Data Scientist?

AspectEntry Level Data Analyst R ProgrammingData Scientist
Required SkillsBasic R programming, data cleaning, visualization, ExcelAdvanced R, Python, machine learning, statistical modeling
Work EnvironmentBusiness, finance, marketing teamsResearch, tech, healthcare, diverse industries
CertificationsData analysis, R programming coursesData science, machine learning certifications

Entry Level Data Analyst R Programming roles focus on data cleaning, visualization, and basic analysis using R, often within business environments. Data Scientists require advanced statistical and programming skills, including machine learning, and work on complex predictive models across various industries. While both roles involve data handling, Data Scientists typically have a broader skill set and handle more complex projects.

What are the most commonly searched types of Data Analyst R Programming jobs in Los Angeles, CA?

The most popular types of Data Analyst R Programming jobs in Los Angeles, CA are:

What are popular job titles related to Entry Level Data Analyst R Programming jobs in Los Angeles, CA?

For Entry Level Data Analyst R Programming jobs in Los Angeles, CA, the most frequently searched job titles are:

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The top searched job categories for Entry Level Data Analyst R Programming jobs in Los Angeles, CA are:

What cities near Los Angeles, CA are hiring for Entry Level Data Analyst R Programming jobs?

Cities near Los Angeles, CA with the most Entry Level Data Analyst R Programming job openings:

Infographic showing various Entry Level Data Analyst R Programming job openings in Los Angeles, CA as of September 2026, with employment types broken down into 1% Internship, 1% As Needed, 83% Full Time, 13% Part Time, and 2% Contract. Highlights an 86% Physical, 3% Hybrid, and 11% Remote job distribution, with an average salary of $73,796 per year, or $35.5 per hour.

BI / Data Analyst

El Segundo, CA โ€ข On-site

AgreeYa Solutions
IT Servicesย โ€ขย 1 - 5K employees

Other

Posted 17 days ago


Job description

Title- Data Analyst/BI Engineer
Location- El Segundo, CA- Hybrid (3 days/week on-site) F2F INTERVIEW
Type- Contract- C2C Works
Duration- 12+ Months


Job Description-
Key Responsibilities
Analyze and integrate data across multiple applications, source systems, and business domains.
Design, build, and maintain scalable data pipelines and transformation logic to support analytics and reporting needs.
Develop advanced SQL queries, analytical models, and reconciliation logic to investigate, validate, and unify complex datasets.
Use Databricks to engineer, transform, optimize, and operationalize large-scale datasets for analytical consumption.
Build curated, business-ready datasets that serve as trusted sources for analysis, executive reporting, and self-service consumption.
Develop and maintain Power BI dashboards and reports that translate complex data into clear, actionable insights for business and executive stakeholders.
Own analytics solutions end to end, from raw data ingestion and transformation through semantic logic, reporting, visualization, and insight generation.
Transform fragmented and complex data into clear, business-relevant stories and recommendations.
Identify relationships between customers, products, locations, revenue, operational activity, and business performance.
Partner with business stakeholders to understand objectives, define KPIs and metrics, and solve challenging business problems.
Investigate data quality issues, perform root-cause analysis, and implement sustainable fixes in partnership with upstream and downstream teams.
Ensure data lineage, business logic, and transformation rules are documented, scalable, and maintainable.
Improve performance, reliability, and usability of analytical workflows using modern engineering and BI best practices.
Continuously expand business, source system, platform, and reporting knowledge to accelerate problem-solving and improve analytical effectiveness.
What Makes Someone Successful in This Role
The strongest individuals in this role are not simply SQL developers, report builders, or dashboard creators. They are end-to-end problem solvers who can connect business needs, data engineering, analytics, and reporting into scalable solutions.
They:
Possess strong analytical curiosity and a desire to deeply understand how the business works.
Have hands-on experience with Databricks, modern data transformation, and analytical data engineering.
Have strong Power BI skills and know how to turn complex analysis into intuitive, executive-friendly dashboards and reporting.
Can connect disparate pieces of information into a complete, accurate, and actionable story.
Are comfortable working through ambiguity and incomplete requirements.
Ask thoughtful questions and challenge assumptions.
Take ownership of finding the right answer, not just the quickest answer.
Understand that trusted analytics begin with well-engineered, validated, and well-modeled data.
Can move seamlessly from raw data to business-ready insight and visualization.
Continuously build expertise in business processes, data lineage, system dependencies, and analytical modeling.
Translate complex technical findings into clear business recommendations and executive-ready outputs.
Demonstrate persistence, intellectual curiosity, and a passion for learning.
Balance speed with rigor, ensuring that solutions are both actionable and sustainable.
Qualifications
Required
Strong SQL development and data analysis experience.
Strong hands-on experience with Databricks for large-scale data processing, transformation, and analytics.
Experience designing and maintaining data pipelines, transformation workflows, and curated analytical datasets.
Strong experience with Power BI (PBI) for dashboard development, data modeling, visualization, and business reporting.
Strong understanding of data engineering concepts, including data lineage, data quality, transformation logic, and scalable data modeling.
Experience working with large and complex datasets across multiple systems.
Strong problem-solving and analytical skills.
Ability to investigate and reconcile data across multiple platforms and source systems.
Experience supporting end-to-end analytics, from raw data ingestion to reporting, dashboarding, and insight generation.
Excellent communication and stakeholder management skills.
Ability to translate business questions into technical, analytical, and reporting solutions.
Preferred
Experience with Snowflake, Python, Spark, Terraform, or enterprise data warehouse environments.
Experience with modern cloud-based analytics platforms and data engineering frameworks.
Knowledge of telecommunications, customer, revenue, operational, or financial data domains.
Experience working with cross-functional teams in a fast-paced environment.
Familiarity with KPI governance, executive reporting, and semantic layer design.