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No Experience Entry Level Data Science Jobs in California

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Data Scientist

San Francisco, CA

Bachelor's or Master's degree in Computer Science, Mathematics, Statistics, or a related field. * Proven experience as a Data Scientist or similar role, preferably in a fast-paced environment.

Adidev Technologies Inc

Data Science

San Francisco, CA · Remote

Adidev Technologies is seeking 1-2 yrs of relevant experience in Data Science. A project can last anywhere from 6 months to 18 months. Salary varies depending on experience, and we are in search of ...

Adidev Technologies Inc

Data Science

San Francisco, CA · On-site

Adidev Technologies is seeking 1-2 yrs of relevant experience in Data Science. A project can last anywhere from 6 months to 18 months. Salary varies depending on experience, and we are in search of ...

Info Way Solutions

Data Science

Fremont, CA · On-site

Info Way Solutions is seeking a Data Science professional to join their team. The role involves ... Responsibilities : • Experience with Statistical Modelling, Data Extraction, Data cleaning, Data ...

Adobe, Inc.

Data Science Engineer

San Jose, CA · On-site

Experience in data cloud platform (eg. Databricks, AWS, Snowflake) * Understanding of machine ... If this role does not have Colorado listed as a hiring location, no specific application window ...

1872 Consulting

Data Science Manager

Santa Clara, CA · On-site

Required : • 6+ of software industry experience in Data Science or Natural Language Processing • 2+ years of experience in managing technical teams or track record of technical leadership ...

LLNL

Data Science Engineer

Livermore, CA · On-site

$121K - $154K/yr

Experience in the space domain, such as space domain awareness, satellite operations, orbital analysis, or applying data science methods to space-related datasets. * Sufficient communication and ...

Leidos

Data Science Intern

San Diego, CA · On-site

$57K - $104K/yr

At our San Diego, CA office, we have a dedicated and experienced team of Scientists and Engineers ... no earlier than 3 days after the original posting date as listed above. Pay Range: Pay Range $57 ...

LLNL

Data Science Engineer

Livermore, CA · On-site

$121K - $154K/yr

Experience in the space domain, such as space domain awareness, satellite operations, orbital analysis, or applying data science methods to space-related datasets. * Sufficient communication and ...

LLNL

Data Science Engineer

Livermore, CA · On-site

$9.7K/wk

Experience in the space domain, such as space domain awareness, satellite operations, orbital analysis, or applying data science methods to space-related datasets. * Sufficient communication and ...

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All JobsData Science JobsNo Experience Entry Level Data Science JobsNo Experience Entry Level Data Science Jobs in California

No Experience Entry Level Data Science information

What is a no experience entry level data science job?

No Experience Entry Level Data Science jobs are positions designed for individuals who are new to the field of data science and may not have any prior professional experience. These roles typically focus on candidates with foundational knowledge of data analysis, statistics, and basic programming skills, often gained through coursework, bootcamps, or self-study. Employers for these positions generally provide training and mentorship, allowing new hires to learn practical data science skills on the job. Such positions are a great way for beginners to gain hands-on experience and start building a career in data science.

What are the key skills and qualifications needed to thrive as a no experience entry level data scientist?

To thrive as a No Experience Entry Level Data Scientist, you need a solid understanding of statistics, basic programming (often Python or R), and foundational knowledge in data analysis, typically supported by a relevant degree or coursework. Familiarity with tools like Excel, Jupyter Notebook, and introductory machine learning libraries such as scikit-learn or pandas is commonly expected. Curiosity, problem-solving skills, and a willingness to learn quickly help candidates stand out in this fast-evolving field. These abilities are crucial for analyzing data effectively, drawing meaningful insights, and adapting to new technologies and challenges in data science roles.

What are common challenges faced by individuals starting in entry-level data science roles with no prior experience?

Individuals beginning in entry-level data science positions without prior experience often face challenges such as getting up to speed with real-world datasets, learning to use industry-standard tools (like Python, SQL, or Tableau), and understanding how to translate business problems into data-driven solutions. Adapting to collaborative work environments, where projects often require teamwork with analysts, engineers, and business stakeholders, can also be a learning curve. However, most organizations provide mentorship and training opportunities to help new hires develop these skills quickly and grow within the team.

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No Experience Entry Level Data Science jobs near you
Infographic showing various No Experience Entry Level Data Science job openings in California as of August 2026, with employment types broken down into 1% As Needed, 76% Full Time, 20% Part Time, and 3% Contract. Highlights an 92% Physical, 2% Hybrid, and 6% Remote job distribution.

Data Scientist - Fraud Detection

DataVisor

Mountain View, CA • On-site

Full-time

Medical, PTO

Posted 7 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

Apply