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Data Science Assistant Jobs in California (NOW HIRING)

LLNL

Data Science Engineer

Livermore, CA · On-site

$121K - $154K/yr

Wehave multiple openings for early-career Data Science Engineers to join a team applying machine ... * Assist in prototyping AI agents and conversational interfaces that allow analysts to query data ...

LLNL

Data Science Engineer

Livermore, CA · On-site

$9.7K/wk

We have multiple openings for early-career Data Science Engineers to join a team applying machine ... * Assist in prototyping AI agents and conversational interfaces that allow analysts to query data ...

LLNL

Data Science Engineer

Livermore, CA

$121K - $154K/yr

We have multiple openings for early-career Data Science Engineers to join a team applying machine ... * Assist in prototyping AI agents and conversational interfaces that allow analysts to query data ...

Superhuman

Director, Data Science

San Francisco, CA · On-site

$302K - $415K/yr

... AI assistant that understands context and delivers help automatically. Refounded in 2025 ... The Opportunity As Director, Data Science , you will lead the data science strategy and team for a ...

Boot Barn

Data Scientist

Irvine, CA · On-site

$100K - $130K/yr

DIRECTOR OF DATA SCIENCE STATUS: EXEMPT Summary Boot Barn is where community comes first. We thrive ... assistants, and multimodal interfaces. * Partner cross-functionally with Store Operations, ...

Boot Barn

Data Scientist

Irvine, CA

$100K - $130K/yr

DIRECTOR OF DATA SCIENCE STATUS: EXEMPT Summary Boot Barn is where community comes first. We thrive ... assistants, and multimodal interfaces. * Partner cross-functionally with Store Operations, ...

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All JobsData Science JobsData Science Assistant JobsData Science Assistant Jobs in California

Data Science Assistant information

What are Data Science Assistants?

Data Science Assistants are professionals who support data scientists and analytics teams by handling tasks such as data collection, data cleaning, preparing datasets, conducting preliminary analyses, and creating visualizations. They often work with large datasets, assist in maintaining data integrity, and help automate routine processes. Their role allows data scientists to focus on more complex modeling and analytical work, making the overall workflow more efficient. Data Science Assistants typically have a foundational understanding of statistics, programming (such as Python or R), and data management tools.

What are the key skills and qualifications needed to thrive as a Data Science Assistant, and why are they important?

To thrive as a Data Science Assistant, you need a solid understanding of statistics, data analysis, and programming (often with a background in mathematics, computer science, or a related field). Familiarity with tools like Python or R, data visualization software, and experience with databases or spreadsheet systems are typically required. Attention to detail, strong problem-solving abilities, and effective communication set outstanding candidates apart. These skills are crucial for supporting data-driven decision-making and ensuring accurate, actionable insights for organizations.

Is 40 too late for data science?

Data Science Assistants and other data science roles do not have strict age limits; many professionals start or transition into data science later in life. Success depends on acquiring relevant skills such as programming, statistics, and machine learning, which can be learned at any age through online courses, certifications, and practical experience.

How does a Data Science Assistant typically collaborate with data scientists and other team members on projects?

As a Data Science Assistant, you will frequently support data scientists by preparing datasets, conducting preliminary data analysis, and creating visualizations. You will often work closely with analysts, engineers, and subject matter experts to gather requirements and ensure data is cleaned and formatted appropriately. Collaboration is a key part of the role, as you may participate in team meetings, share findings, and help with documentation to keep projects running smoothly. This supportive environment provides an excellent opportunity to learn from experienced professionals and gain exposure to the full data science workflow.

What is the 80 20 rule in data science?

In data science, the 80/20 rule, also known as the Pareto principle, suggests that roughly 80% of the results come from 20% of the efforts or data. Data scientists often use this concept to focus on the most impactful features, data subsets, or tasks to improve model performance efficiently.

What is the difference between Data Science Assistant vs Data Analyst?

AspectData Science AssistantData Analyst
Required CredentialsBachelor's in Data Science, Statistics, or related fieldBachelor's in Statistics, Mathematics, or related field
Work EnvironmentTech companies, research labs, data-driven departmentsBusiness, finance, marketing, healthcare sectors
Employer & Industry UsageUsed in data science teams for supporting models and analysisUsed across industries for interpreting data and generating reports

While both roles involve working with data, a Data Science Assistant typically supports data science projects, focusing on data preparation and model testing. A Data Analyst primarily interprets data to generate insights and reports. The roles overlap in skills and work environments but differ in their core responsibilities and focus areas.

What do data assistants do?

Data Science Assistants support data analysis by collecting, cleaning, and organizing data sets. They often use tools like Excel, SQL, or Python to prepare data for modeling and reporting, assisting data scientists and analysts in project workflows.

Can I get a data scientist job with no experience?

Entry-level data science assistant roles often do not require prior experience, but candidates typically need a strong foundation in programming (such as Python or R), statistics, and data analysis. Gaining relevant skills through online courses, certifications, or personal projects can improve chances of securing such positions.
What are the most commonly searched types of Data Science jobs in California? The most popular types of Data Science jobs in California are:
What are popular job titles related to Data Science Assistant jobs in California? For Data Science Assistant jobs in California, the most frequently searched job titles are:
What job categories do people searching Data Science Assistant jobs in California look for? The top searched job categories for Data Science Assistant jobs in California are:
What cities in California are hiring for Data Science Assistant jobs? Cities in California with the most Data Science Assistant job openings:
Data Science Assistant jobs near you
Infographic showing various Data Science Assistant job openings in California as of July 2026, with employment types broken down into 1% As Needed, 76% Full Time, 19% Part Time, 1% Temporary, and 3% Contract. Highlights an 98% Physical, 1% Hybrid, and 1% Remote job distribution.
Data Science intern

Data Science intern

DEUNA

San Francisco, CA • On-site

Temporary

Posted 26 days ago

Job description

About DEUNA
DEUNA is a rapidly growing startup revolutionizing global commerce with ATHIA, our AI-powered orchestration and payments platform that helps large enterprises boost approval rates, reduce costs, and unlock new revenue. Built by the team behind DEUNA-the fastest-growing Commerce OS in Latin America-ATHIA combines payment intelligence, checkout optimization, and data orchestration in one powerful solution.
With deep integrations across 300+ PSPs and alternative payment methods, and over 20% of Mexico's digital economy running through our platform, we simplify global payments through a single integration and centralized reconciliation.
We are a rapidly growing startup expanding into the U.S. to meet the urgent needs of large retailers, marketplaces, airlines, and QSRs. Join us to shape the future of payments!
Visit https://www.deuna.com/ to learn more about us!
We are looking for curious, analytical, and motivated students who are eager to learn about Data Science in a fast-paced technology environment. During the internship, you will support the Data team by analyzing data, building models, developing insights, and contributing to projects that have a direct impact on our products and business.
This is an educational, unpaid internship designed to provide practical experience, mentorship, and exposure to real-world data science projects.
Key Responsibilities
  • Assist in collecting, cleaning, and preparing datasets for analysis.
  • Perform exploratory data analysis to identify trends and patterns.
  • Support the development and evaluation of machine learning models.
  • Build dashboards and visualizations to communicate business insights.
  • Collaborate with Data Scientists, Data Engineers, and Product teams on ongoing initiatives.
  • Document analyses, methodologies, and project findings.
  • Participate in team meetings, knowledge-sharing sessions, and technical discussions.
  • Learn and apply best practices in data science, experimentation, and analytics.
Qualifications
Required
  • Currently pursuing a Bachelor's or Master's degree in:
    • Computer Science
    • Data Science
    • Statistics
    • Mathematics
    • Engineering
    • Economics
    • Physics
    • Or a related quantitative field.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

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