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Entry Level Data Scientist Jobs in California (NOW HIRING)

Entry Level Data Scientiest

Los Angeles, CA · On-site

$18 - $24/hr

Identify valuable data sources and automate collection processes * Undertake preprocessing of ... Bachelors, Masters in Computer Science/ Computer Engineering/ Information Systems/Information ...

... GenAI Data Scientist - Manager, you will play a pivotal role in transforming raw data into ... PwC does not intend to hire experienced or entry level job seekers who will need, now or in the ...

... GenAI Data Scientist - Manager, you will play a pivotal role in transforming raw data into ... PwC does not intend to hire experienced or entry level job seekers who will need, now or in the ...

... GenAI Data Scientist - Manager, you will play a pivotal role in transforming raw data into ... PwC does not intend to hire experienced or entry level job seekers who will need, now or in the ...

... GenAI Data Scientist - Manager, you will play a pivotal role in transforming raw data into ... PwC does not intend to hire experienced or entry level job seekers who will need, now or in the ...

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 ...

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Entry Level Data Scientist information

See California salary details

$45.4K

$162.9K

$240.3K

How much do entry level data scientist jobs pay per year?

As of Aug 30, 2026, the average yearly pay for entry level data scientist in California is $162,857.00, according to ZipRecruiter salary data. Most workers in this role earn between $131,800.00 and $167,800.00 per year, depending on experience, location, and employer.

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

AspectEntry Level Data ScientistData Analyst
Required CredentialsBachelor's in CS, Statistics, or related field; some knowledge of programming and machine learningBachelor's in Business, Statistics, or related field; strong Excel, SQL, and visualization skills
Work EnvironmentCollaborates with data science teams, uses programming languages like Python or R, focuses on predictive modelingWorks with business teams, uses SQL, Excel, and BI tools, focuses on reporting and data visualization
Employer & Industry UsageTech companies, finance, healthcare, startupsRetail, marketing, finance, healthcare, government

Entry Level Data Scientists and Data Analysts often share foundational skills like SQL and data visualization. However, data scientists typically focus on building predictive models and machine learning algorithms, requiring programming knowledge, while data analysts concentrate on interpreting data through reports and dashboards. Both roles are essential in data-driven organizations but differ in technical depth and project scope.

Can an entry level data scientist be entry-level?

Yes, an entry-level data scientist position is designed for individuals starting their careers in data science, often requiring minimal professional experience and foundational skills in programming, statistics, and data analysis tools. These roles typically focus on learning and developing skills such as Python, R, SQL, and machine learning basics under supervision.

How to get an entry level data scientist job with no experience?

To secure an entry-level data scientist position with no experience, focus on building a strong foundation in programming languages like Python or R, and learn key tools such as SQL and machine learning libraries. Completing relevant online courses, earning certifications, and working on personal or open-source projects can demonstrate skills to employers. Internships, volunteering, or participating in data competitions also provide practical experience and improve job prospects.
More about Entry Level Data Scientist jobs

What are the most commonly searched types of Data Scientist jobs in California?

The most popular types of Data Scientist jobs in California are:

What cities in California are hiring for Entry Level Data Scientist jobs?

Cities in California with the most Entry Level Data Scientist job openings:

Infographic showing various Entry Level Data Scientist job openings in California as of August 2026, with employment types broken down into 1% As Needed, 79% Full Time, 15% Part Time, and 5% Contract. Highlights an 84% Physical, 4% Hybrid, and 12% Remote job distribution, with an average salary of $162,857 per year, or $78.3 per hour.

Data Scientist - Fraud Detection

DataVisor

Mountain View, CA • On-site

Full-time

Medical, PTO

Posted 5 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