Post job

Production scientist vs data scientist

The differences between production scientists and data scientists can be seen in a few details. Each job has different responsibilities and duties. It typically takes 2-4 years to become both a production scientist and a data scientist. Additionally, a data scientist has an average salary of $106,104, which is higher than the $77,464 average annual salary of a production scientist.

The top three skills for a production scientist include process improvement, QC and lab equipment. The most important skills for a data scientist are python, data science, and visualization.

Production scientist vs data scientist overview

Production ScientistData Scientist
Yearly salary$77,464$106,104
Hourly rate$37.24$51.01
Growth rate17%16%
Number of jobs100,301106,973
Job satisfaction--
Most common degreeBachelor's Degree, 83%Bachelor's Degree, 51%
Average age4141
Years of experience44

What does a production scientist do?

A production scientist analyzes production operations and manufacturing processes to identify gaps, modify current procedures that would increase process efficiency, and maximize optimal performance. Production scientists inspect the tools and materials utilized for the production and oversee research trials for process formulations. They also develop opportunities and design models that support business functions, generating more innovation and increasing more revenue resources for the business. A production scientist writes research findings, manages resources, and determines various process feasibility.

What does a data scientist do?

A Data Scientist analyzes information from multiple sources in order to gain maximum insight that can give the company a competitive advantage. They work in different domains, including manufacturing, healthcare, education, and finance.

Production scientist vs data scientist salary

Production scientists and data scientists have different pay scales, as shown below.

Production ScientistData Scientist
Average salary$77,464$106,104
Salary rangeBetween $48,000 And $124,000Between $75,000 And $148,000
Highest paying CitySouth San Francisco, CARichmond, CA
Highest paying stateCaliforniaCalifornia
Best paying companyBeckman CoulterThe Citadel
Best paying industryHealth CareStart-up

Differences between production scientist and data scientist education

There are a few differences between a production scientist and a data scientist in terms of educational background:

Production ScientistData Scientist
Most common degreeBachelor's Degree, 83%Bachelor's Degree, 51%
Most common majorBiologyComputer Science
Most common collegeUniversity of Southern CaliforniaColumbia University in the City of New York

Production scientist vs data scientist demographics

Here are the differences between production scientists' and data scientists' demographics:

Production ScientistData Scientist
Average age4141
Gender ratioMale, 58.4% Female, 41.6%Male, 79.6% Female, 20.4%
Race ratioBlack or African American, 6.1% Unknown, 4.0% Hispanic or Latino, 9.3% Asian, 23.3% White, 57.1% American Indian and Alaska Native, 0.1%Black or African American, 4.2% Unknown, 5.4% Hispanic or Latino, 6.9% Asian, 18.8% White, 64.2% American Indian and Alaska Native, 0.6%
LGBT Percentage8%9%

Differences between production scientist and data scientist duties and responsibilities

Production scientist example responsibilities.

  • Manage a team focuse on genotyping, purification, and quantitation assays, including training of new scientists.
  • Develop and manage third party claim investigations and contractor remedial oversight for various insurance companies.
  • Follow current GMP, GDP and FDA regulations to maintain documentation and improve work instructions.
  • Extract biological samples and analyze via HPLC and LC/MS/MS analysis in accordance with GLP regulations.
  • Acquire good laboratory practice (GLP) and good manufacturing practice (GMP) in industry.
  • Direct technology transfer from bench top to pilot scale and then to production scale at CMO.
  • Show more

Data scientist example responsibilities.

  • Update, maintain, and manage regional CRM database and records for customers, vendors, and suppliers.
  • Configure and manage JobScope ERP system for a make-to-order/make-to-stock design and manufacturing environment.
  • Lead the analysis in SAS for data integration of mortality data using meta-analysis integration methods.
  • Implement a proximal stochastic gradient descent with a line search to fit a regularize logistic regression in Scala
  • Perform cross-validation-test on linear regression model of data using scikit-learn.
  • Develop python base statistical visualization to provide insights of fuzzy social media data.
  • Show more

Production scientist vs data scientist skills

Common production scientist skills
  • Process Improvement, 14%
  • QC, 8%
  • Lab Equipment, 7%
  • GMP, 6%
  • Molecular Biology, 4%
  • PCR, 4%
Common data scientist skills
  • Python, 13%
  • Data Science, 10%
  • Visualization, 5%
  • Java, 4%
  • Hadoop, 4%
  • Tableau, 3%

Browse life, physical, and social science jobs