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Data Science Assistant Jobs (NOW HIRING)

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Data Scientist

San Francisco, CA

Document methodologies and processes to ensure that data science projects are scalable and sustainable. * Assist in the data governance process to ensure data accuracy and integrity. Requirements

New

Figma

Director, Data Science

San Francisco, CA · On-site +1

Shape how we measure AI products: evals, quality, and experimentation for LLM-powered assistants ... high output Data Science teams, with at least 2 years managing other managers * 7+ years of ...

NCSU

Data Science Librarian

Raleigh, NC · On-site

The Data Science Services (DSS) department (6 librarians, 1 library specialist, plus graduate student assistants) helps students and other researchers develop critical data science and visualization ...

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 ...

Athenago

Data Science Intern

Wilmington, DE

We clear the way by pairing exceptional Executive Assistants with our driven clients, providing ... Role Overview The Data Science Intern will help us to understand the performance of Executive ...

Athena LLC

We clear the way by pairing exceptional Executive Assistants with our driven clients, providing ... Role Overview The Data Science Intern will help us to understand the performance of Executive ...

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 ...

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Data Science Assistant information

What is a data science assistant?

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?

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.

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.

More about Data Science Assistant jobs
What cities are hiring for Data Science Assistant jobs? Cities with the most Data Science Assistant job openings:
What are the most commonly searched types of Data Science jobs? The most popular types of Data Science jobs are:
What states have the most Data Science Assistant jobs? States with the most job openings for Data Science Assistant jobs include:
What job categories do people searching Data Science Assistant jobs look for? The top searched job categories for Data Science Assistant jobs are:
Data Science Assistant jobs near you
Infographic showing various Data Science Assistant job openings in the United States as of August 2026, with employment types broken down into 6% Internship, 79% Full Time, 9% Part Time, 3% Temporary, and 3% Contract. Highlights an 94% In-person, and 6% Remote job distribution.

Data Scientist

Find Data Science

San Francisco, CA

Full-time

Posted 2 days ago

New

Job description

Data Scientist - San Francisco

We are seeking a talented and experienced Data Scientist to join our dynamic team in San Francisco. As a Data Scientist, you will play a pivotal role in harnessing data to drive strategic decision-making processes and enhance our product offerings. You will work within a collaborative, innovative environment where your insights will shape our business strategies and help us remain competitive in an increasingly data-driven world.

Your expertise in data analysis, machine learning, and statistical modeling will enable you to tackle complex business challenges. By transforming raw data into actionable insights, you will directly contribute to our mission of providing exceptional products and services that meet the needs of our clients and customers.

Key Responsibilities
  • Analyze large datasets to uncover trends, patterns, and insights that will inform business strategies.
  • Develop, implement, and maintain advanced machine learning models to optimize company performance.
  • Collaborate with cross-functional teams to integrate data-driven solutions into existing business processes.
  • Create visualizations and dashboards to present findings to various stakeholders effectively.
  • Conduct experiments and statistical analysis to evaluate the effectiveness of business strategies.
  • Stay updated on industry trends and best practices regarding data science methodologies and technologies.
  • Mentor junior data analysts and contribute to the development of their technical skills.
  • Document methodologies and processes to ensure that data science projects are scalable and sustainable.
  • Assist in the data governance process to ensure data accuracy and integrity.
Requirements
  • 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.
  • Strong proficiency in programming languages such as Python or R.
  • Experience with data visualization tools (e.g., Tableau, Power BI) and SQL.
  • Solid understanding of machine learning algorithms and statistical analysis techniques.
  • Excellent analytical and problem-solving skills with a keen attention to detail.
  • Strong communication skills, with the ability to convey complex data insights to non-technical audiences.
  • Ability to work collaboratively in a team-oriented environment.
  • Experience with big data technologies (e.g., Hadoop, Spark) is a plus.