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Data Scientist Biochemistry Jobs (NOW HIRING)

Performs complex statistical analysis of data collected and writes interpretative reports. Verifies the correctness of the data submitted and makes recommendations based on these analyses.

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The Data Scientist is expected to prototype and design to the goals of functionality and ... Familiarity with or interest in biology, microbiology and biochemistry * Proficient analytical ...

The Data Scientist is expected to prototype and design to the goals of functionality and ... Familiarity with or interest in biology, microbiology and biochemistry * Proficient analytical ...

Description bioMerieux's Data Science group is looking for an experienced Data Scientist to help ... Familiarity with or interest in biology, microbiology and biochemistry * Proficient analytical ...

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Data Scientist Biochemistry information

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$37.5K

$122.7K

$196.5K

How much do data scientist biochemistry jobs pay per year?

As of Jun 12, 2026, the average yearly pay for data scientist biochemistry in the United States is $122,738.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,500.00 and $136,000.00 per year, depending on experience, location, and employer.

What does a biomedical data scientist do?

A biomedical data scientist analyzes complex biological and medical data to identify patterns, develop models, and support research or clinical decisions. They often use statistical tools, programming languages like Python or R, and work with large datasets from experiments, genomics, or electronic health records to advance healthcare and biomedical understanding.

How does a Data Scientist in Biochemistry typically collaborate with laboratory researchers and other scientific teams?

As a Data Scientist in Biochemistry, you'll frequently work alongside laboratory researchers, chemists, and biologists to interpret experimental results and develop data-driven insights. Collaboration often involves translating complex biological questions into computational problems, analyzing large datasets from experiments, and communicating findings in a way that supports ongoing research. Effective teamwork and clear communication are crucial, as you'll help bridge the gap between experimental science and analytical modeling, ensuring that data analyses are aligned with scientific objectives.

Is 30 too late for data science?

For a Data Scientist in biochemistry, starting a career at age 30 is not too late. Many professionals transition into data science later in life, and skills such as programming, statistical analysis, and domain knowledge can be developed through online courses and certifications regardless of age.

Can I become a data scientist with a biochemistry degree?

A biochemistry degree provides a strong foundation for a data scientist role, especially when combined with skills in programming, statistics, and data analysis tools like Python or R. Many data scientists have diverse academic backgrounds and acquire relevant technical skills through online courses or certifications to transition into the field.

What is the highest paid job in biochemistry?

In biochemistry, the highest paid roles are often senior research directors, pharmaceutical executives, or biotech company leaders, with salaries exceeding $150,000 annually. These positions typically require advanced degrees, extensive experience, and strong leadership skills, often involving strategic decision-making and management of large teams or projects.

What are the key skills and qualifications needed to thrive as a Data Scientist in Biochemistry, and why are they important?

To thrive as a Data Scientist in Biochemistry, you need a strong background in biochemistry or molecular biology, advanced statistical analysis, and programming skills (often with a master's or Ph.D. in a related field). Familiarity with tools such as Python, R, machine learning frameworks, and bioinformatics databases is typically required, along with experience using laboratory data management systems. Exceptional problem-solving, critical thinking, and communication skills set candidates apart, enabling them to interpret complex biological data and collaborate across scientific teams. These skills are crucial for transforming raw biochemical data into actionable insights that drive research and innovation in life sciences.

What does a Data Scientist in Biochemistry do?

A Data Scientist in Biochemistry applies data analysis, machine learning, and statistical techniques to large sets of biochemical data. They work with experimental results, genomic sequences, protein structures, and other biological datasets to uncover patterns, make predictions, and support scientific discoveries. Their work often involves collaboration with biochemists to design experiments, interpret results, and contribute to advancements in areas like drug discovery and understanding disease mechanisms.

What is the difference between Data Scientist Biochemistry vs Data Analyst Biochemistry?

AspectData Scientist BiochemistryData Analyst Biochemistry
Required CredentialsDegree in Biochemistry, Data Science, or related fields; proficiency in programming and statistical toolsDegree in Biochemistry, Life Sciences, or related fields; basic data analysis skills
Work EnvironmentResearch labs, biotech companies, pharmaceutical firms, often involving complex data modelingLaboratories, research institutions, healthcare settings, focusing on data reporting and visualization
Employer & Industry UsageUsed in biotech, pharma, research institutions for advanced data modeling and predictive analyticsCommon in healthcare, research labs for data reporting, trend analysis, and basic statistical tasks

While both roles require a background in biochemistry, Data Scientist Biochemistry focuses on advanced data modeling, machine learning, and predictive analytics, often requiring programming skills. Data Analysts Biochemistry primarily handle data reporting, visualization, and basic statistical analysis. The roles differ mainly in complexity and technical expertise, but both are vital in biotech and healthcare industries.

More about Data Scientist Biochemistry jobs
What cities are hiring for Data Scientist Biochemistry jobs? Cities with the most Data Scientist Biochemistry job openings:
What states have the most Data Scientist Biochemistry jobs? States with the most job openings for Data Scientist Biochemistry jobs include:

Sr. Research Scientist - Biochemistry

Sovereign Technologies

Wilmington, DE

$95K - $121K/yr

Other

Posted 4 days ago


Job description

Job Title: Sr. Research Scientist – Biochemistry
Location: Onsite, Wilmington, DE

Position Overview

We are seeking a highly skilled Sr. Research Scientist – Biochemistry to support drug discovery efforts through the design, development, and execution of biochemical and biophysical assays. This role will play a critical part in hit identification, validation, and mechanistic studies for small molecules and other therapeutic modalities.

Key Responsibilities

  • Design, develop, and execute biochemical assays (e.g., FI, HTRF, FP) and biophysical assays (e.g., SPR, BLI, ITC, DSF)
  • Conduct high-throughput screening (HTS) to evaluate compound libraries and characterize binding kinetics (IC₅₀, Kd, kon, koff)
  • Troubleshoot assay performance, optimizing for robustness, reproducibility, and scalability
  • Analyze and interpret experimental data using tools such as GraphPad Prism and Genedata
  • Support protein expression and purification workflows using chromatography techniques (affinity, ion-exchange, size-exclusion)
  • Operate and maintain lab instrumentation including plate readers and automated liquid handling systems
  • Maintain accurate documentation using electronic lab notebooks (ELN) and contribute to technical reports and presentations

Required Qualifications

  • Bachelor’s, Master’s, or Ph.D. in Biochemistry, Chemistry, Biophysics, Chemical Biology, or related field
  • Strong foundation in enzymology and assay development
  • Hands-on experience in protein purification and biochemical/biophysical characterization
  • Proficiency with data analysis tools (GraphPad Prism, Genedata, or similar)
  • Experience working in a laboratory setting with strong attention to detail and documentation