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Entry Level Data Analyst R Programming Jobs in Hayward, CA

1.    Strong in advance SQL 2.    Good at data analysis 3.    Should be able to build BI dashboards using Tableau & Power BI 4.    Candidate should be able to assist ...

Operations Data Analyst

Oakland, CA · On-site

$77 - $82/hr

Bachelor's degree in Data Analytics, Statistics, Computer Science, Business, Engineering, or a related field (or equivalent experience). * Demonstrated experience building and maintaining dashboards ...

... or engineering. • Substantial experience with MS Office and analytical programs. • Strong ... Preferred : • Proficiency in Python, R, Linux, and command line tools. • A strong background in ...

Senior Support Data Analyst

Oakland, CA · On-site

$98K - $124K/yr

Fivetran helps organizations automate data movement across the systems, clouds, engines, and tools they rely on. dbt Labs pioneered analytics engineering, helping teams transform data into reliable ...

Showing results 41-60

Entry Level Data Analyst R Programming information

See Hayward, CA salary details

$15

$37

$70

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

As of Sep 1, 2026, the average hourly pay for entry level data analyst r programming in Hayward, CA is $37.75, according to ZipRecruiter salary data. Most workers in this role earn between $24.23 and $42.16 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.

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

What job categories do people searching Entry Level Data Analyst R Programming jobs in Hayward, CA look for?

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

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

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

Infographic showing various Entry Level Data Analyst R Programming job openings in Hayward, CA as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 15% Part Time, and 2% Contract. Highlights an 86% Physical, 3% Hybrid, and 11% Remote job distribution, with an average salary of $78,520 per year, or $37.8 per hour.

Data Scientist - Fraud Detection

DataVisor

Mountain View, CA • On-site

Full-time

Medical, PTO

Posted 6 days ago


Job description

About DataVisor:
DataVisor is the world's leading AI-powered Fraud and Risk Platform that delivers the best overall detection coverage in the industry. With an open SaaS platform that supports easy consolidation and enrichment of any data, DataVisor's fraud and anti-money laundering (AML) solutions scale infinitely and enable organizations to act on fast-evolving fraud and money laundering activities in real time. Its patented unsupervised machine learning technology, advanced device intelligence, powerful decision engine, and investigation tools work together to provide significant performance lift from day one. DataVisor's platform is architected to support multiple use cases across different business units flexibly, dramatically lowering total cost of ownership, compared to legacy point solutions. DataVisor is recognized as an industry leader and has been adopted by many Fortune 500 companies across the globe.

Our award-winning software platform is powered by a team of world-class experts in big data, machine learning, security, and scalable infrastructure. Our culture is open, positive, collaborative, and results-driven. Come join us!

Position Overview:

We are looking for a motivated Entry-Level Data Scientist to join our Fraud Detection team. In this role, you will leverage your machine learning and data analysis skills to identify fraudulent activities, build predictive models, and uncover hidden patterns in large datasets. You will work closely with cross-functional teams to develop scalable solutions that enhance our fraud detection capabilities. This is a great opportunity to grow your skills in a fast-paced, data-driven environment while making a real impact in the fight against fraud.

Key Responsibilities:

  • Develop and deploy machine learning models for fraud detection and risk assessment.
  • Perform exploratory data analysis (EDA) to identify trends, anomalies, and patterns in transactional data.
  • Clean, preprocess, and analyze large datasets using Python and popular data science libraries (pandas, NumPy, scikit-learn, etc.).
  • Collaborate with engineering and business teams to integrate ML models into production systems.
  • Continuously monitor model performance and refine algorithms to improve accuracy.
  • Stay updated with the latest advancements in fraud detection techniques and ML/AI technologies.

Requirements

  • Master's degree in Computer Science, Data Science, Statistics, or a related quantitative field. Ph.D. degree is a plus. 
  • Strong programming skills in Python and familiarity with data science libraries (NumPy, Pandas, scikit-learn, TensorFlow/PyTorch is a plus).
  • Solid understanding of machine learning algorithms (supervised/unsupervised learning, anomaly detection, classification, etc.).
  • Experience with SQL and data manipulation/analysis in large datasets.
  • Strong problem-solving skills and patience for deep-dive data exploration.
  • Prior internship or project experience in fraud modeling, risk analysis, or related fields is a plus.
  • Excellent communication skills and ability to work in a collaborative environment.
Nice to have
  • Familiarity with big data tools (Spark, Hadoop, Dask).
  • Knowledge of graph-based fraud detection techniques.
  • Experience with cloud platforms (AWS, GCP, Azure).

Benefits

PTO, Stock Option, Health Benefits