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Entry Level Data Science Jobs in Castro Valley, CA

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 ...

Pwc

AI & GenAI Data Scientist - Manager

San Francisco, CA · On-site

$99K - $232K/yr

Management Information Systems, Computer and Information Science, Systems Engineering, Mathematics ... PwC does not intend to hire experienced or entry level job seekers who will need, now or in the ...

New

Eurofins

Packaging Testing Technician

San Jose, CA · On-site

$20 - $24.25/hr

Company Description Eurofins Scientific is an international life sciences company, providing a ... Prepare Test Evidence Report. * Entry level data review and data reporting, following good ...

Tryfacta, Inc.

Student/Graduate Intern

San Jose, CA · On-site

$28.27 - $32.27/hr

The Information Systems Analyst Intern will perform entry-level professional work supporting the ... Data Science * Related technical field Preferred Academic Focus: * Computer Science * Information ...

Tredence Inc.

Call Center Representative

San Jose, CA

$60.21/hr

Are you ready to be part of a dynamic team at a globally recognized leader in data science ... This entry-level role is perfect for individuals who are eager to kickstart their career in a fast ...

New

Tredence Inc.

Accounts Receivable AR Clerk

San Jose, CA

$64.17/hr

Join Tredence , a global leader in data science solutions and AI-driven decision intelligence. With ... an entry-level role where we value your enthusiasm and willingness to learn! Why Tredence? At ...

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Entry Level Data Science information

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How much do entry level data science jobs pay per hour?

As of Aug 28, 2026, the average hourly pay for entry level data science in Castro Valley, CA is $21.99, according to ZipRecruiter salary data. Most workers in this role earn between $18.61 and $24.66 per hour, depending on experience, location, and employer.

What is an entry level data scientist?

Entry level data science jobs are positions designed for individuals who are starting their careers in the field of data science, often requiring minimal professional experience. These roles typically involve working with data collection, cleaning, and analysis, as well as assisting more senior data scientists with projects. Entry level data scientists are expected to have a foundational understanding of statistics, programming (often in Python or R), and basic machine learning concepts. They may work in various industries, helping organizations gain insights from data to support decision-making.

What types of projects or tasks can I expect to work on as an entry level data scientist?

As an entry-level data scientist, you'll typically work on tasks such as data cleaning, exploratory data analysis, and supporting the development of predictive models. You may also assist in preparing datasets, generating reports, and visualizing data for stakeholders. Collaboration with more senior data scientists and cross-functional teams like engineering or business analysts is common, giving you opportunities to learn and grow your technical and communication skills. These foundational projects are essential for building your expertise and preparing for more complex responsibilities as you advance in your career.

What are the key skills and qualifications needed to thrive as an entry level data scientist, and why are they important?

To thrive as an Entry Level Data Scientist, you need a strong background in statistics, programming (often Python or R), and data analysis, typically supported by a relevant degree such as computer science, mathematics, or statistics. Familiarity with technical tools like SQL databases, data visualization software (e.g., Tableau), and machine learning libraries (such as scikit-learn or TensorFlow) is commonly expected. Curiosity, problem-solving ability, and effective communication help you interpret data insights and collaborate with diverse teams. These skills ensure you can extract meaningful insights from data, contribute to data-driven decision-making, and grow within the analytics field.

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

AspectEntry Level Data ScienceData Analyst
Required CredentialsBachelor's in CS, Statistics, or related field; some certificationsBachelor's in Business, Statistics, or related field; certifications optional
Work EnvironmentTech companies, startups, research labsBusiness, marketing, finance sectors
Employer & Industry UsageData-driven roles in tech and researchBusiness insights, reporting, and visualization
Common Search & ComparisonYesYes

Entry Level Data Science and Data Analyst roles often share similar educational backgrounds and work environments. However, data scientists typically focus on building models and advanced analytics, while data analysts concentrate on interpreting data and creating reports. Both roles are essential in data-driven organizations, but they differ in technical complexity and scope.

Are there entry-level data science roles?

Yes, entry-level data science roles are available and typically require foundational skills in programming, statistics, and data analysis, often using tools like Python or R. These positions are suitable for recent graduates or those transitioning into data science and may involve internships or junior analyst roles to gain experience.

How to start a career in entry level data science with no experience?

To start a career in entry level data science with no experience, focus on building foundational skills in programming languages like Python or R, and learn data analysis and visualization tools such as SQL and Tableau. Completing online courses, earning certifications, and working on personal projects or internships can demonstrate your abilities to employers and help you gain practical experience.

What are the most commonly searched types of Data Science jobs in Castro Valley, CA?

The most popular types of Data Science jobs in Castro Valley, CA are:

What are popular job titles related to Entry Level Data Science jobs in Castro Valley, CA?

For Entry Level Data Science jobs in Castro Valley, CA, the most frequently searched job titles are:

What job categories do people searching Entry Level Data Science jobs in Castro Valley, CA look for?

The top searched job categories for Entry Level Data Science jobs in Castro Valley, CA are:

What cities near Castro Valley, CA are hiring for Entry Level Data Science jobs?

Cities near Castro Valley, CA with the most Entry Level Data Science job openings:

Entry Level Data Science jobs near you
Infographic showing various Entry Level Data Science job openings in Castro Valley, CA as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 14% Part Time, and 3% Contract. Highlights an 84% Physical, 4% Hybrid, and 12% Remote job distribution, with an average salary of $45,729 per year, or $22 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

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