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Postdoctoral Data Scientist Jobs in California (NOW HIRING)

23andme

Scientist, Population Genetics

Palo Alto, CA · On-site

Synergistically combine array-based genotyping and sequencing data in your work. * Develop methods ... Some postdoctoral or industry experience. * San Francisco Bay Area location, or willingness to ...

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Postdoctoral Data Scientist information

What is a postdoctoral data scientist?

A Postdoctoral Data Scientist is a researcher who has completed their doctoral studies (PhD) and is engaged in advanced research and analysis involving large data sets. They often work in academic, government, or industry settings, applying statistical, computational, and machine learning techniques to solve complex problems. Their work may involve developing new methodologies, publishing research findings, and collaborating with interdisciplinary teams. Postdoctoral Data Scientists typically aim to expand their expertise and contribute to scientific knowledge before moving to more permanent positions.

What are some typical collaborative projects a postdoctoral data scientist might work on within a research team?

As a Postdoctoral Data Scientist, you can expect to work closely with both academic researchers and industry professionals on interdisciplinary projects. These collaborations often involve designing and implementing advanced data analysis pipelines, developing machine learning models, and interpreting complex datasets to extract actionable insights. You may also co-author scientific papers, contribute to grant proposals, and present findings at conferences. Collaboration is crucial, as you will regularly share your expertise with other scientists and provide guidance on best practices in data management and analysis.

What are the key skills and qualifications needed to thrive as a postdoctoral data scientist, and why are they important?

To thrive as a Postdoctoral Data Scientist, you need advanced statistical analysis, machine learning expertise, and a PhD in a quantitative field such as computer science, statistics, or engineering. Familiarity with programming languages like Python or R, data visualization tools, and experience with big data platforms are typically required. Strong problem-solving, communication, and project management skills help you effectively collaborate across disciplines and present complex findings. These skills ensure you can drive impactful research, translate data into actionable insights, and contribute to scientific and organizational goals.

What is the difference between Postdoctoral Data Scientist vs Data Scientist?

AspectPostdoctoral Data ScientistData Scientist
Required CredentialsPhD in Data Science, Computer Science, or related fieldBachelor's or Master's degree in relevant field, often with industry experience
Work EnvironmentAcademic or research institutions, labsCorporate, tech companies, startups
Employer & Industry UsageResearch-focused roles, academia collaborationsProduct development, analytics, business intelligence
Common Search & ComparisonResearch, academic projects, postdoctoral rolesIndustry projects, data analysis, machine learning applications

Postdoctoral Data Scientists typically hold a PhD and work in research or academic settings, focusing on advanced data analysis and experimentation. Data Scientists usually have a bachelor's or master's degree and work in industry, applying data analysis and machine learning to solve business problems. The roles differ mainly in work environment and experience level, but both require strong analytical skills and familiarity with data tools.

What are popular job titles related to Postdoctoral Data Scientist jobs in California?

For Postdoctoral Data Scientist jobs in California, the most frequently searched job titles are:

What job categories do people searching Postdoctoral Data Scientist jobs in California look for?

The top searched job categories for Postdoctoral Data Scientist jobs in California are:

What cities in California are hiring for Postdoctoral Data Scientist jobs?

Cities in California with the most Postdoctoral Data Scientist job openings:

Postdoctoral Data Scientist jobs near you
Infographic showing various Postdoctoral Data Scientist job openings in California as of August 2026, with employment types broken down into 1% As Needed, 88% Full Time, 9% Part Time, and 2% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution.

Postdoctoral Scientist - Dyadic Research

Cedars Sinai

Los Angeles, CA • On-site

$62K - $93K/yr

Full-time

Re-posted 11 days ago

Key responsibilities

  • Lead and conduct advanced statistical analyses using dyadic and multilevel modeling methodologies for cancer prevention and control research studies.

  • Collaborate with the Principal Investigator and research team to support study design, protocol development, and interpretation of complex research findings.

  • Analyze hierarchical and interdependent data structures to address health disparities and inform intervention development.

Cedars-Sinai rating

8.6

Company rating: 8.6 out of 10

Based on 131 frontline employees who took The Breakroom Quiz

43rd of 1,065 rated hospitals

Job description


Working independently but in close cooperation and in consultation with the Principal Investigator and other Research Scientists, the Postdoctoral Scientist will perform routine and complex laboratory procedures throughout training period. May develop, adapt, and implement new research techniques and protocols.
Analyzes and interprets data. May assist in preparation of grant proposals. Participates in publications and presentations as author or co-author. Not responsible for generating grant funds.
As a Postdoctoral Scientist, you will be a vital member of Dr. Tan's interdisciplinary research team, which includes biostatisticians, qualitative research specialists, and grant administration and project management professionals. Responsibilities include leading quantitative and qualitative research projects, supporting participant engagement efforts, and fostering strong partnerships with community stakeholders and collaborators.
This role follows a hybrid work schedule; however, we can only consider applicants who will be able to commute to our Los Angeles work location a few times per week. If hired you must reside in the commutable area.
The Postdoctoral Scholar will lead advanced quantitative analyses using dyadic and multilevel modeling approaches to support innovative cancer prevention and control research within the Tan Lab at Cedars-Sinai. This role focuses on addressing health disparities and advancing research initiatives related to lung cancer survivorship, prostate cancer shared decision making, smoking cessation, and pancreatic cancer intervention development. Working closely with the Principal Investigator, the scholar will contribute to high-impact publications, grant-supported research activities, and the development of evidence-based interventions that improve patient outcomes across diverse populations.
Primary Duties and Responsibilities
  • Establish and maintain lab and study-specific SOP
  • Provides timely and constructive feedback to study team.
  • Delegate responsibilities to team members to efficiently execute research protocols and procedures.
  • Experience working in interdisciplinary and transdisciplinary teams.
  • May assist in the preparation of grant proposals, but is not responsible for generating grant funds.
  • May participate in publications and presentations as author or co-author.
  • Designs and performs experiments. Will keep appropriate experimental records and documentation and analyze the results with the Principal Investigator (PI).
  • May develop, adapt, and implement new research techniques and protocols.
  • Analyzes interpret, summarizes, and compiles data.
  • Performs routine and complex laboratory procedures throughout the training period.
  • Operates and maintains equipment and instruments.
  • May observe PI-patient or PI-human research subject interactions as it pertains directly to research being performed.

Day-to-Day Responsibilities
  • Lead and conduct advanced statistical analyses utilizing dyadic matched-pairs and multilevel modeling methodologies for cancer prevention and control research studies.
  • Collaborate with the Principal Investigator and research team to support study design, protocol development, and interpretation of complex research findings.
  • Analyze hierarchical and interdependent data structures to address health disparities and inform intervention development.
  • Support ongoing research initiatives related to lung cancer survivorship, prostate cancer shared decision making, smoking cessation, and pancreatic cancer interventions.
  • Prepare manuscripts, abstracts, presentations, and other scholarly materials for publication and scientific dissemination.
  • Contribute to grant proposal preparation and other research-related funding activities.
  • Maintain organized research workflows, support laboratory operations, and ensure timely execution of project deliverables.
  • Participate in interdisciplinary collaboration with faculty, clinicians, and research staff to advance the Cancer Center's research mission.

Qualifications
This role follows a hybrid work schedule; however, we can only consider applicants who will be able to commute to our Los Angeles work location a few times per week. If hired you must reside in the commutable area.
Requirements:
  • Doctorate (MD, PhD, VMD, or DDS) in area directly related to field of research specialization.
  • Only applicants who submit a cover letter with their application materials will be considered for this opportunity.
  • 1 year, acquires thorough technical and theoretical knowledge of research project and objectives during one to five (1-5) year post-doctoral appointment.

Preferred:
  • Demonstrated expertise in dyadic data analysis, matched-pairs research design, and multilevel modeling techniques.
  • Experience conducting quantitative research in cancer prevention, survivorship, behavioral interventions, or health disparities research.
  • Strong proficiency with statistical software packages such as R, SAS, SPSS, Stata, or Mplus.
  • Proven track record of scholarly productivity, including peer-reviewed publications and scientific presentations.
  • Experience supporting or contributing to grant-funded research activities and manuscript development.
  • Strong analytical, organizational, and communication skills with the ability to manage multiple research priorities in a collaborative academic environment.
  • Ability to work independently while contributing effectively within a multidisciplinary research team.

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