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Internship Reddit Data Science Jobs in California

Data Scientist

Berkeley, CA · On-site

$150 - $190/hr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

... internships working with complex datasets, including curation, querying, aggregation, exploratory ... Bachelor's degree in a quantitative discipline (statistics, biostatistics, data science, computer ...

DATA SCIENTIST I-FINANCIAL & TIME SERIES FORE

Norco, CA · On-site

$34.62 - $45.67/hr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

Bachelor's degree in Mathematics, Statistics, Computer Science, Data Science, Economics, Finance ... Academic, internship, research, or project experience involving statistical modeling, machine ...

Data Scientist, Core Data - PhD (2026)

San Francisco, CA · On-site +1

$178K/yr

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

Publications or research experience in experimentation or applied ML; industry internship experience applying data science to product or business problems * An AI-native mindset, with exposure to or ...

Senior Data Scientist

Palo Alto, CA · Remote

$198K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

About You * 4-5 years of hands-on experience in data science, applied statistics, or machine learning (internships and projects count). * Familiarity and experience working with AI toolkits such as ...

Showing results 41-60

Internship Reddit Data Science information

What are the key skills and qualifications needed to thrive as an internship Reddit data science?

To thrive as a Reddit Data Science intern, you need a solid background in statistics, programming (Python or R), and data analysis, usually supported by progress toward a degree in a quantitative field. Familiarity with tools such as SQL, Jupyter Notebooks, and machine learning libraries like scikit-learn or TensorFlow is typically required. Strong problem-solving abilities, curiosity, and effective communication skills help interns collaborate and present data-driven insights. These skills are crucial for extracting actionable information from Reddit's large datasets, driving informed decisions, and contributing to product and user experience improvements.

What is an internship Reddit data science position?

An Internship Reddit Data Science position is a temporary role where students or recent graduates work with Reddit's data science team. Interns assist with analyzing large datasets, building models, and deriving insights to improve user experience and business outcomes. The role typically involves working with programming languages like Python or R, using tools for data analysis and visualization, and collaborating with other engineers and data scientists. It's a valuable opportunity for gaining hands-on experience in real-world data science projects within a dynamic tech company. The internship can help build skills and open doors for future careers in data science.

What is the difference between Internship Reddit Data Science vs Data Analyst Intern?

AspectInternship Reddit Data ScienceData Analyst Intern
Required skillsBasic programming, statistics, data manipulationData visualization, Excel, SQL, basic statistics
Work environmentTech companies, startups, online platformsBusiness, finance, marketing sectors
Typical tasksData cleaning, model development, analysisReporting, dashboards, data interpretation
Common industry usageTech, social media, online communitiesCorporate, marketing, finance

Internship Reddit Data Science and Data Analyst Intern roles share foundational skills like data manipulation and basic analytics. However, Reddit Data Science internships focus more on developing models and working with large datasets in tech environments, while Data Analyst Internships emphasize reporting and visualization in business contexts. Both roles provide valuable experience but cater to different career paths within data fields.

What types of projects and responsibilities can I expect as a data science intern at Reddit?

As a Data Science Intern at Reddit, you can expect to work on a variety of projects ranging from analyzing user engagement data to building predictive models that support product and content recommendations. You'll collaborate closely with data scientists, engineers, and product managers, often using tools like Python, SQL, and machine learning libraries. Common responsibilities include cleaning and visualizing data, conducting exploratory analysis, and presenting insights to stakeholders. This hands-on experience will help you develop both technical and communication skills in a dynamic, team-oriented environment.

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

The most popular types of Reddit Data Science jobs in California are:

What job categories do people searching Internship Reddit Data Science jobs in California look for?

The top searched job categories for Internship Reddit Data Science jobs in California are:

What cities in California are hiring for Internship Reddit Data Science jobs?

Cities in California with the most Internship Reddit Data Science job openings:

Infographic showing various Internship Reddit Data Science job openings in California as of August 2026, with employment types broken down into 16% Internship, 65% Full Time, and 19% Part Time. Highlights an 90% In-person, and 10% Remote job distribution.

Biostatistics Scientist (Plant Science)

Sakata Seed America, INC.

Woodland, CA • On-site

$90K - $105K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 19 days ago


Job description


JOB SUMMARY

The Biostatistics Scientist supports applied statistical analysis, quantitative genetics, and breeding analytics for vegetable crop research programs. This entry-level role contributes to genomic, phenotypic, and field-trial data analysis under the guidance of senior scientists, managers and cross-functional project teams. The position helps develop reliable, reproducible analytical workflows that improve trait evaluation, marker-assisted selection, genomic prediction, and data-driven breeding decisions.

Key Responsibilities

Statistical Analysis, Quantitative Genetics & Genomic Prediction

  • Support the development, testing, and interpretation of statistical and genomic prediction models for vegetable crop breeding programs.
  • Apply standard statistical and quantitative genetics methods, such as mixed models, heritability estimation, genetic correlations, and basic genomic prediction approaches.
  • Assist with evaluating model performance, prediction accuracy, and data quality across populations, environments, and breeding stages.
  • Contribute to analyses that help breeders understand trait variation, experimental results, and selection opportunities.
  • Document methods, assumptions, code, and results clearly to support reproducibility and team review.

Molecular Marker & Trait Analytics

  • Analyze molecular marker datasets, including SNP and haplotype data, to support trait mapping, marker validation, and breeding decisions.
  • Assist molecular and breeding teams with data summaries for marker development, marker deployment, and trait evaluation projects.
  • Support quality control of genotypic and phenotypic datasets, including data cleaning, formatting, consistency checks, and basic exploratory analysis.
  • Help prepare selection metrics, trait summaries, and visualizations that integrate multiple sources of breeding data.
  • Translate analytical results into concise summaries that can be reviewed by breeders, molecular scientists, and project teams.

Genomic, Phenotypic & Field Trial Data Analysis

  • Prepare, manage, and analyze genomic, phenotypic, greenhouse, and field-trial datasets under guidance from senior team members.
  • Develop and maintain reproducible scripts for data quality control, statistical analysis, visualization, and reporting.
  • Contribute to the improvement of analytical templates, reporting workflows, and shared data practices in collaboration with bioinformatics and data teams.

Project Support & Cross-Functional Collaboration

  • Support analytical components of breeding, trait development, molecular marker, and technology projects.
  • Collaborate with breeders, phenotyping, molecular biology, bioinformatics, and data teams to understand project objectives and data requirements.
  • Prepare clear technical summaries, tables, figures, and presentations to communicate results to internal stakeholders.
  • Learn and apply current methods in biostatistics, quantitative genetics, breeding analytics, and reproducible scientific computing.


Required Qualifications

Education

  • PhD in Biostatistics, Statistics, Quantitative Genetics, Plant Breeding, Computational Biology, Data Science, or a related field; industry experience a plus
    or
  • MS in Biostatistics, Statistics, Quantitative Genetics, Plant Breeding, Computational Biology, Data Science, or a related field with 0–2 years of relevant academic, internship; industry experience a plus


Experience & Technical Skills

  • Foundational training in statistics, biostatistics, quantitative genetics, plant breeding, computational biology, or related analytical disciplines.
  • Experience with statistical analysis of biological, genomic, phenotypic, field-trial, or experimental datasets through graduate research, internships, or applied projects.
  • Working knowledge of statistical programming in R, Python, SAS, or similar tools.
  • Good understanding of experimental design, mixed models, regression, data visualization, and reproducible analytical workflows.
  • Experience with molecular markers, genomic data, plant breeding concepts, or trait analysis is desirable.
  • Ability to learn new methods, manage multiple analytical tasks, and deliver accurate results with guidance.
  • Strong attention to detail, scientific curiosity, communication skills, and willingness to collaborate across disciplines.

Preferred Qualifications

  • Research experience in plant breeding, seed industry research, agricultural biotechnology, or applied life-science data analysis.
  • Experience in genomic prediction, QTL mapping, GWAS, marker-assisted selection, or trait discovery workflows.
  • Familiarity with breeding databases, phenotyping systems, laboratory information systems, or integrated data platforms.
  • Experience preparing figures, tables, dashboards, or technical reports for scientific or cross-functional audiences.
  • Exposure to cloud-based, Linux, Git, or high-performance computing environments for data analysis.
  • Interest in applying AI, machine learning, and modern statistical methods to practical breeding and research questions.

Competencies & Behaviors

  • Demonstrates curiosity, initiative, and accountability in learning new analytical methods and scientific workflows.
  • Applies statistical methods carefully, with attention to data quality, assumptions, and reproducibility.
  • Works collaboratively with scientists from breeding, molecular biology, phenotyping, bioinformatics, and data teams.
  • Communicates analytical results clearly to both technical and non-technical audiences.
  • Manages assigned tasks effectively, asks timely questions, and follows through on deliverables.
  • Contributes to a culture of scientific rigor, continuous improvement, teamwork, and practical problem solving.

Reporting Structure

  • Reports to Senior Biotech Manager

Works under the guidance of senior scientists, project leads, and cross-functional research teams

BENEFITS:

Health & Wellness
Medical, Dental & Vision Insurance
Monthly Wellness Stipend
Employee Assistance Program (EAP)

Employee Philanthropic Giving Program

Disability Insurance (plans vary by location)


Financial Benefits
401(k) Program + Company Match
Profit Sharing Program (via 401(k)

Holiday Bonus

Performance Incentive Bonus Program
Tuition Reimbursement

529 College‑Savings Plan
Company-Paid Basic Life & AD&D Insurance


Time Off & Flexibility
Paid Vacation
Paid Sick Leave
15 Paid Company Holidays
2 Floating Holidays

Birthday Off