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Data Scientist Biochemistry Jobs (NOW HIRING)

bioMerieux

Sr. Data Scientist

Hazelwood, MO

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

Illumina, Inc.

Sr Biochemistry Scientist

Madison, WI · On-site

$92K - $126K/yr

You are the Senior Biochemistry Scientist Illumina is looking for in joining our Test Method ... Perform data processing, statistical evaluation, and interpretation of experimental results.

Eurofins

Scientist - Data Review

Columbia, MO · On-site

Eurofins BPT-Columbia is looking for a Scientist, Data Review tojoin our Quality Assurance team ... Bachelor's degree in relevant field such as chemistry, biochemistry, biology, chemical engineering ...

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Data Scientist Biochemistry information

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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
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What states have the most Data Scientist Biochemistry jobs? States with the most job openings for Data Scientist Biochemistry jobs include:
What job categories do people searching Data Scientist Biochemistry jobs look for? The top searched job categories for Data Scientist Biochemistry jobs are:
Data Scientist Biochemistry jobs near you
Data Scientist - I (Assistant)

Data Scientist - I (Assistant)

Talent Software Services

Rahway, NJ • Hybrid

Other

Posted 16 days ago

Job description

Data Scientist – Contractor (Quantitative Biosciences) Location: Rahway, NJ (Hybrid: 3 days onsite, 2 days remote) Overview Join a cutting-edge and innovative Quantitative Biosciences department focused on advancing drug discovery through computational science, high-throughput experimentation, and multidisciplinary collaboration. We apply robust scientific methodologies, translational models, and advanced automation to better understand biological systems and molecular mechanisms, enabling the development of next-generation medicines. This role offers the opportunity to work on complex, high-dimensional biological data across multiple modalities, directly supporting biologists and chemists in early-stage drug discovery.

Qualifications Minimum Education: Bachelor’s degree in Computational Physics, Chemistry, Bioinformatics, Computer Science, or another relevant quantitative field. Advanced Degrees (acceptable): Master’s or PhD in Computational Physics, Chemistry, Bioinformatics, Computer Science, or related disciplines. Experience: 0–3 years of relevant experience.

Required Skills Proficiency in Python for scientific computing (e.g., NumPy, PyTorch, SciPy, pandas). Experience with high-performance computing (HPC) in Unix/Linux environments or cloud platforms (e.g., AWS). Hands-on experience in data science and machine learning.

Working knowledge of biochemistry and/or chemistry. Nice to Have Experience in pharmaceutical early drug discovery research. Exposure to advanced machine learning applications, especially in drug discovery contexts.

Experience developing large-scale chemical foundation models, virtual screening models, or protein structure prediction models. Responsibilities As a Data Scientist within the Quantitative Biosciences team, you will: Develop machine learning and deep learning workflows to support novel drug discovery. Build and improve property prediction models for small molecules and peptides.

Collaborate with interdisciplinary teams to apply computational and statistical methods for drug target identification and lead optimization. Analyze complex, high-throughput experimental datasets across multiple biological modalities. Conduct research in machine learning, molecular modeling, and computational biology.

Communicate insights and analytical results clearly to scientific stakeholders, both verbally and in writing. Support experimental design by providing data-driven interpretation and guidance. Role Summary This role is ideal for candidates who are intellectually curious and interested in the intersection of machine learning, computational science, and drug discovery, with opportunities for growth in a highly collaborative research environment.

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