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Entry Level Data Jobs in Sunnyvale, CA (NOW HIRING)

SynergisticIT

data (Entry Level)

San Francisco, CA · On-site

$20 - $26.75/hr

From staffing to full implementation of projects we provide the highest quality IT Services. We Focus on Java/Full stack and Data Science/Machine learning/Python/AI candidates. You'll be responsible ...

Eurofins

Packaging Testing Technician

San Jose, CA · On-site

$20 - $24.25/hr

Prepare Test Evidence Report. * Entry level data review and data reporting, following good documentation practices * Maintain Records of Packaging Testing. * Monitor and Provide customer support ...

ZL Technologies

Entry-Level Accountant

Milpitas, CA · On-site

We are seeking a detail-oriented and motivated Entry-Level Accountant to join our Finance team ... Maintain accounting records and ensure data accuracy in the ERP/accounting system. * Collaborate ...

ZL Technologies

Entry-Level Accountant

Milpitas, CA

We are seeking a detail-oriented and motivated Entry-Level Accountant to join our Finance team ... Maintain accounting records and ensure data accuracy in the ERP/accounting system. * Collaborate ...

PDS Services

Data Collection Operator

San Francisco, CA · On-site

$23/hr

... entry-level robotics experience who are comfortable standing for long periods and performing ... Your movements generate critical data that helps engineers and developers design, teach, and ...

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Entry Level Data information

See Sunnyvale, CA salary details

$12

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How much do entry level data jobs pay per hour?

As of Aug 29, 2026, the average hourly pay for entry level data in Sunnyvale, CA is $22.85, according to ZipRecruiter salary data. Most workers in this role earn between $19.18 and $25.67 per hour, depending on experience, location, and employer.

What is an entry level data job?

Entry level data jobs are positions designed for individuals who are new to the data field, often requiring minimal professional experience. These roles may include titles such as Data Analyst, Data Coordinator, or Junior Data Scientist. Responsibilities typically involve data cleaning, basic analysis, reporting, and supporting more senior data professionals. Entry level data jobs are a great way to build foundational skills in data manipulation, visualization, and interpretation using tools like Excel, SQL, or Python. They are commonly found in industries such as finance, healthcare, retail, and technology.

What are the key skills and qualifications needed to thrive as an entry level data analyst?

To thrive as an Entry Level Data Analyst, you need foundational skills in data analysis, statistics, and problem-solving, typically supported by a relevant degree such as in mathematics, statistics, or computer science. Familiarity with tools like Microsoft Excel, SQL, and data visualization platforms (e.g., Tableau or Power BI) is often required, along with basic programming knowledge in Python or R. Strong attention to detail, analytical thinking, and effective communication are valuable soft skills for interpreting and sharing data-driven insights. These abilities are important to accurately analyze data, support business decisions, and collaborate with team members across departments.

What types of projects or tasks are typically assigned to entry level data professionals during their first year?

Entry-level data professionals often start by working on data cleaning, validation, and basic analysis tasks, helping to ensure data quality and accuracy for the team. They may assist with preparing reports, creating simple visualizations, or supporting more senior analysts with larger projects. These tasks help build foundational skills in data manipulation and provide exposure to the company's data systems and tools. Collaboration with other team members, such as analysts, engineers, and business stakeholders, is common and fosters a supportive learning environment.

What is the difference between Entry Level Data vs Data Analyst?

AspectEntry Level DataData Analyst
Required CredentialsHigh school diploma or associate's; some roles may prefer certificationsBachelor's degree in data-related fields; certifications like SQL or Excel often preferred
Work EnvironmentEntry-level roles in various industries, often in office settings or remoteOffice-based, collaborative environment; may involve client interaction
Employer & Industry UsageFound across industries; entry positions for those starting in data rolesCommon in finance, healthcare, marketing, and tech sectors

Entry Level Data roles are typically for individuals starting their data careers with basic skills and minimal experience, often focusing on data entry or simple analysis. Data Analysts usually have more specialized training and experience, handling complex data analysis, reporting, and insights. Both roles are essential in data-driven organizations, but Data Analysts generally require a higher skill set and educational background.

What are the most commonly searched types of Data jobs in Sunnyvale, CA?

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

What cities near Sunnyvale, CA are hiring for Entry Level Data jobs?

Cities near Sunnyvale, CA with the most Entry Level Data job openings:

Entry Level Data jobs near you
Infographic showing various Entry Level Data job openings in Sunnyvale, CA as of August 2026, with employment types broken down into 1% As Needed, 84% Full Time, 11% Part Time, and 4% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution, with an average salary of $47,538 per year, or $22.9 per hour.

Data Scientist - Fraud Detection

DataVisor

Mountain View, CA • On-site

Full-time

Medical, PTO

Posted 3 days ago

New

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

Apply