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Data Visualization Engineer Jobs in Roseville, CA

Penumbra

Principal Quality Engineer

Roseville, CA · On-site

$135K - $175K/yr

... and automated data visualization tools. * Lead highcomplexity problem-solving efforts using ... Bachelor's degree in Engineering (Biomedical, Mechanical, Materials, Chemical, or related ...

Penumbra

Principal Quality Engineer

Roseville, CA · On-site

$135K - $175K/yr

... data visualization tools. * Lead high‑complexity problem-solving efforts using advanced ... Bachelor's degree in Engineering (Biomedical, Mechanical, Materials, Chemical, or related ...

West Advanced Technologies (WATI)

Data Modeler

Sacramento, CA · On-site

$50.75 - $65.75/hr

Three (3) years of demonstrated experience building reporting/visualization, including dashboards ... DevOps and Microsoft Azure Cloud technologies. Education: Bachelors Degree in Information ...

Pwc

ERP AI Engineer - Manager

Sacramento, CA · On-site

$99K - $232K/yr

... Data Visualization, and Oracle Machine Learning. Enhancing your leadership style, you motivate ... The Opportunity As part of the Data and Analytics Engineering team, you will serve as both a ...

Agilent

IBP Supply Planning Data Scientist

Folsom, CA · On-site

Proficiency in programming languages such as Python, R, or SQL. * Experience with data visualization tools like Tableau, Power BI, Qlik, Spotfire or similar. * Strong analytical and problem-solving ...

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All JobsData Visualization Engineer JobsData Visualization Engineer Jobs in Roseville, CA

Data Visualization Engineer information

See Roseville, CA salary details

$46.6K

$136K

$186.1K

How much do data visualization engineer jobs pay per year?

As of Sep 6, 2026, the average yearly pay for data visualization engineer in Roseville, CA is $135,976.00, according to ZipRecruiter salary data. Most workers in this role earn between $120,000.00 and $144,100.00 per year, depending on experience, location, and employer.

What is a data visualization engineer?

A Data Visualization Engineer is responsible for designing, developing, and implementing visual representations of data to help stakeholders understand complex information. They use tools like Tableau, D3.js, Power BI, and Python libraries (e.g., Matplotlib, Seaborn) to create interactive dashboards and reports. Their role involves working with large datasets, ensuring data accuracy, optimizing performance, and collaborating with analysts and developers to enhance decision-making. Strong programming, data analysis, and UX/UI design skills are essential for success in this role.

What are some common challenges faced by data visualization engineers, and how can they overcome them?

Data Visualization Engineers often encounter challenges such as translating complex data into clear, actionable visuals for non-technical stakeholders and ensuring that graphics remain both accurate and engaging. Balancing the needs of different departments, adhering to fluctuating project requirements, and managing large or messy datasets can also be demanding. Successful engineers address these issues by working closely with data analysts, business users, and designers, using feedback to iterate on their work, and staying current with the latest visualization best practices. Proactive communication and strong organization skills further help in meeting deadlines and maintaining quality standards.

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

To thrive as a Data Visualization Engineer, you need a strong grasp of data analysis, visual storytelling, and programming, often supported by a degree in computer science, data science, or a related field. Familiarity with tools like Tableau, Power BI, D3.js, and proficiency in languages such as Python or JavaScript are commonly required, along with experience in databases and dashboard development. Strong communication, problem-solving, and collaboration skills help you effectively transform and present complex data to diverse audiences. These abilities are crucial for creating impactful, user-friendly visualizations that drive informed business decisions.

What are popular job titles related to Data Visualization Engineer jobs in Roseville, CA?

For Data Visualization Engineer jobs in Roseville, CA, the most frequently searched job titles are:

What job categories do people searching Data Visualization Engineer jobs in Roseville, CA look for?

The top searched job categories for Data Visualization Engineer jobs in Roseville, CA are:

What cities near Roseville, CA are hiring for Data Visualization Engineer jobs?

Cities near Roseville, CA with the most Data Visualization Engineer job openings:

Data Visualization Engineer jobs near you
Infographic showing various Data Visualization Engineer job openings in Roseville, CA as of August 2026, with employment types broken down into 1% As Needed, 83% Full Time, 13% Part Time, and 3% Contract. Highlights an 88% Physical, 3% Hybrid, and 9% Remote job distribution, with an average salary of $135,976 per year, or $65.4 per hour.

Biostatistics Scientist (Plant Science)

Sakata Seed America, INC.

Woodland, CA • On-site

$90K - $105K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 10 days ago

Key responsibilities

  • Support the development, testing, and interpretation of statistical and genomic prediction models for vegetable crop breeding programs.

  • Analyze molecular marker datasets, including SNP and haplotype data, to support trait mapping, marker validation, and breeding decisions.

  • Prepare, manage, and analyze genomic, phenotypic, greenhouse, and field-trial datasets under guidance from senior team members.

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