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Data Science Assistant Jobs in California (NOW HIRING)

Sedgwick

Data Scientist

Los Angeles, CA · On-site

Execute data science projects as identified by Sr Data Scientists, leadership, and stakeholders ... Produce reports to communicate metrics and outcomes of stakeholder interest * Assist with ...

Rich Data Co

Senior Data Scientist

San Jose, CA

With built-in AI assistants and clear rationales for every recommendation, we empower banks across ... AI is a cloud native AI Decisioning company and the Data Science function is key to our ...

Buck Institute

AI Data Scientist-Furman lab

Novato, CA · On-site

$60K - $75K/yr

... data science. This position is ideal for a creative, technically outstanding individual with a ... Developing systems that assist with literature mining, data annotation, hypothesis generation, and ...

BIOMARIN PHARMACEUTICAL

Data Scientist 2

Novato, CA · On-site

This role blends advanced technical skills in Data Science-covering statistics, Modelling, AI/ML ... Develop GenAI solutions (e.g., RAG for SOPs/reports, Semantic search, Q&A assistants over technical ...

Align Technology

Sr. Data Scientist

San Jose, CA · On-site

$158K - $218K/yr

... assist teams to drive the company's product development roadmap and transform the orthodontic world with the Invisalign product. Role expectations * Act as a senior data science expert within R&D, ...

Figma

Technical Program Manager, Data Science

San Francisco, CA · Remote

$152K - $196K/yr

... Figma Data Assistant, while building the operational foundation for a growing DS org. This is a ... Work closely with peer TPMs & Data Scientists (AI, Infra, Performance) to coordinate on overlapping ...

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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 can enter the field at any age, as success depends on skills, experience, and continuous learning. Many professionals transition into data science later in their careers by acquiring relevant knowledge in programming, statistics, and tools like Python or R. Age is not a barrier if you develop the necessary competencies and stay current with industry trends.

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 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 is a data scientist assistant?

A data scientist assistant supports data scientists by collecting, cleaning, and analyzing data, often using tools like Python or R. They help prepare reports, build models, and may need knowledge of statistics and data visualization to contribute effectively to data projects.

Is AI replacing data scientists?

AI is transforming the role of data scientists by automating routine tasks such as data cleaning and basic analysis, but it does not replace the need for skilled professionals to interpret results, develop models, and make strategic decisions. Data scientists are increasingly required to work alongside AI tools, focusing on complex problem-solving, model development, and domain expertise. Continuous learning and proficiency in programming languages like Python and tools such as machine learning frameworks remain essential for the role.

Which is better, DS or CS?

For a Data Science Assistant role, both Data Science (DS) and Computer Science (CS) provide valuable skills; DS focuses on data analysis, modeling, and visualization, while CS emphasizes algorithms, programming, and software development. The choice depends on the specific job requirements and your career goals, but familiarity with programming languages like Python or R and understanding of data tools are essential in both fields.
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 June 2026, with employment types broken down into 1% As Needed, 86% Full Time, 11% Part Time, 1% Temporary, and 1% Contract. Highlights an 98% Physical, 1% Hybrid, and 1% Remote job distribution.
Data Scientist

Data Scientist

Sedgwick

Los Angeles, CA • On-site

Other

Medical, Dental, Vision, Retirement, PTO

Posted 4 days ago

Sedgwick rating

7.5

Company rating: 7.5 out of 10

Based on 308 frontline employees who took The Breakroom Quiz

187th of 261 rated insurance

Job description

By joining Sedgwick, you'll be part of something truly meaningful. It's what our 33,000 colleagues do every day for people around the world who are facing the unexpected. We invite you to grow your career with us, experience our caring culture, and enjoy work-life balance. Here, there's no limit to what you can achieve.

Newsweek Recognizes Sedgwick as America's Greatest Workplaces National Top Companies

Certified as a Great Place to Work

Fortune Best Workplaces in Financial Services & Insurance

Data Scientist
Job Description

Primary Purpose of this Role: To develop and manage predictive modeling assignments through completion; to communicate results; to make recommendations to management; and to ensure model ownership, implementation, and monitoring; to spot trends and to gain maximum insight that can give the company a competitive advantage.

Essential Responsibilities May Include

  • Execute data science projects as identified by Sr Data Scientists, leadership, and stakeholders

  • Help to build, prototype, and deploy machine learning models in sandbox and production environments

  • Produce reports to communicate metrics and outcomes of stakeholder interest

  • Assist with developing and maintaining end-to-end ETL data pipelines

  • Work to explore new internal data sources and their utility within projects

  • Communicate modeling challenges, findings, and outcomes to stakeholders

Qualifications

  • Insurance claims knowledge required

  • Minimum one year of predictive modeling, data science, and analysis experience with solid background in the using data visualization tools and libraries and data exploration, data wrangling, and feature engineering

  • Experience writing Python or R code, and notebook environments

  • Knowledge of writing code in Python or R, and notebook environments

  • Knowledge of common unsupervised/supervised ML techniques

Taking Care of You

  • Career development and promotional growth opportunities

  • A diverse and comprehensive benefits offering including medical, dental vision, 401k, PTO and more

The statements contained in this document are intended to describe the general nature and level of work being performed by a colleague assigned to this description. They are not intended to constitute a comprehensive list of functions, duties, or local variances. Management retains the discretion to add or to change the duties of the position at any time.

Sedgwickis an Equal Opportunity Employer and a Drug-Free Workplace.

If you're excited about this role but your experience doesn't align perfectly with every qualification in the job description, consider applying for it anyway! Sedgwick is building a diverse, equitable, and inclusive workplace and recognizes that each person possesses a unique combination of skills, knowledge, and experience. You may be just the right candidate for this or other roles.

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