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Assistant Genomics Data Scientist Jobs (NOW HIRING)

In this role, you will work at the intersection of machine learning, genomics, and clinical science ... Strong expertise in data analysis using Python or R * Deep understanding of modern machine learning ...

The Lead Bioinformatics AI Scientist will play a central role in AI-powered genomics research and data analysis, focusing on identifying novel AI solutions, training and fine-tuning GenAI models ...

In this role, you will work at the intersection of machine learning, genomics, and clinical science ... Strong expertise in data analysis using Python or R * Deep understanding of modern machine learning ...

In this role, you will work at the intersection of machine learning, genomics, and clinical science ... Strong expertise in data analysis using Python or R * Deep understanding of modern machine learning ...

Summary We are seeking a human genetics data scientist to join the Human Genetics & Targets group ... Experience processing and analyzing biobank-scale genomic data (e.g. UK Biobank, All of Us, FinnGen ...

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How much do assistant genomics data scientist jobs pay per year?

As of Jul 13, 2026, the average yearly pay for assistant genomics data scientist in the United States is $165,018.00, according to ZipRecruiter salary data. Most workers in this role earn between $133,500.00 and $170,000.00 per year, depending on experience, location, and employer.

What does an Assistant Genomics Data Scientist do?

An Assistant Genomics Data Scientist supports research and analysis by managing, processing, and interpreting large-scale genomic datasets. They use bioinformatics tools, statistical methods, and programming languages such as Python or R to help identify patterns and insights in genetic data. Their work often contributes to projects in healthcare, pharmaceuticals, or academic research, assisting senior scientists in making sense of complex biological information. Additionally, they may help maintain data pipelines and ensure the quality and integrity of genomic databases.

What are the key skills and qualifications needed to thrive as an Assistant Genomics Data Scientist, and why are they important?

To thrive as an Assistant Genomics Data Scientist, you need a background in bioinformatics, statistics, and molecular biology, often supported by a relevant degree. Familiarity with programming languages such as Python or R, experience with genomic databases, and knowledge of tools like BLAST and GATK are typically required. Strong analytical thinking, attention to detail, and effective communication skills help you interpret complex data and collaborate with multidisciplinary teams. These competencies are essential for accurately analyzing genomic datasets and translating findings into actionable scientific insights.

What are some common challenges faced by Assistant Genomics Data Scientists when working with large-scale genomic datasets?

Assistant Genomics Data Scientists often encounter challenges related to managing and analyzing massive genomic datasets, which can require specialized computational tools and robust data storage solutions. Ensuring data quality and integrity while dealing with issues such as missing values, sequencing errors, or inconsistent formats is also common. Additionally, collaborating with interdisciplinary teams of biologists, clinicians, and senior data scientists requires strong communication skills to translate complex findings into actionable insights. Adapting to rapidly evolving technologies and staying current with best practices in bioinformatics is essential for success in this role.
What cities are hiring for Assistant Genomics Data Scientist jobs? Cities with the most Assistant Genomics Data Scientist job openings:
What are the most commonly searched types of Genomics Data Scientist jobs? The most popular types of Genomics Data Scientist jobs are:
What states have the most Assistant Genomics Data Scientist jobs? States with the most job openings for Assistant Genomics Data Scientist jobs include:
Senior Data Scientist Immunotherapy Platform

Senior Data Scientist Immunotherapy Platform

MD Anderson Center

Houston, TX • On-site

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 4 days ago

New


MD Anderson Cancer Center rating

8.4

Company rating: 8.4 out of 10

Based on 169 frontline employees who took The Breakroom Quiz

27th of 882 rated healthcare providers


Job description

UT MD Anderson is a leading institution focused on cancer care, research, education, and prevention. UT MD Anderson is dedicated to advancing scientific discovery and translating breakthrough research into impactful therapies for patients worldwide. The Senior Data Scientist (Data Infrastructure & Engineering) plays a critical role within the Immunotherapy Platform (IMT), supporting multi-modal cancer research through the development of scalable and robust data systems. The Senior Data Scientist (Data Infrastructure & Engineering) will lead efforts to integrate diverse biomedical datasets into a unified ecosystem, while the Senior Data Scientist (Data Infrastructure & Engineering) also collaborates closely with researchers and computational teams to enable efficient, AI-ready workflows.
Ideal candidate has experience developing AI-ready models and scalable computational data pipelines, with strong ability to collaborate across multidisciplinary teams to support complex research and data infrastructure needs. Experience working in a academic or healthcare environment.
Why Us?
This role offers the opportunity to build foundational data systems that directly enable cutting-edge cancer immunotherapy research at UT MD Anderson. By contributing to scalable, AI-ready data infrastructure, individuals in this role will have a meaningful impact on accelerating scientific discovery while developing advanced technical expertise in a collaborative and innovation-driven environment that supports professional growth and work-life balance.
• Employer-paid medical coverage starting day one for employees working 30+ hours/week, plus optional group dental, vision, life, AD&D, and disability insurance.
• Accruals for PTO and Extended Illness Bank, plus paid holidays, wellness, childcare, and other leave options.
• Tuition Assistance Program after six months of service and access to extensive wellness, fitness, and employee resource groups.
• Defined-benefit pension through the Teachers Retirement System, voluntary retirement plans, and employer-paid life and reduced salary protection programs.
Responsibilities
Data Infrastructure & Engineering
• Design and implement biomedical data systems for multi-modal datasets including genomic, single-cell, spatial, proteomic, and clinical data
• Develop and maintain an internal data registry and metadata tracking systems
• Design databases and data models using SQL/NoSQL technologies, schema design, and APIs
• Harmonize and standardize data across datasets and platforms
Pipeline Development & Systems
• Develop pipelines for data ingestion, transformation, and integration using ETL/ELT processes
• Utilize workflow orchestration tools such as Nextflow and Snakemake
• Apply strong programming skills in Python, with R as a plus
• Leverage HPC and/or cloud-based environments for scalable processing
• Implement version control and reproducible workflows using Git and container technologies
• Enable lightweight data access and integration with visualization tools or internal data portals
Project Development
• Design and implement a centralized internal data system for IMT
• Develop and enforce standardized data schemas across modalities
• Enable efficient querying, access, and reuse of datasets
• Collaborate with computational scientists to support analysis and modeling workflows
• Optimize data pipelines to improve scalability and reduce turnaround time
• Establish best practices for data governance, documentation, and reproducibility
• Support development of internal data access interfaces such as portals or dashboards
Research Support
• Support integration of multi-modal datasets for downstream analysis
• Enable data structures compatible with AI and machine learning workflows
• Collaborate with research teams to translate analytical needs into scalable systems
• Evaluate and adopt emerging tools and standards in biomedical data infrastructure
• Contribute to publications through development of computational workflows and systems
Other duties as assigned.
EDUCATION:
Required: Bachelor's Degree Biomedical Engineering, Electrical Engineering, Computer Engineering, Physics, Applied Mathematics, Science, Engineering, Computer Science, Statistics, Computational Biology, or related field. Master's Degree Science, Engineering or related field. PhD Science, Engineering or related field.
EXPERIENCE:
Required: Five years experience in scientific software or industry programming with a concentration in scientific computing. With Master's degree, three years experience. With PhD, one year experience.
Preferred:
Experience working with biomedical or genomics data in healthcare or academic environment. Experience with AI models. Experience computational pipelines. Experience supporting research or analytical teams.
The University of Texas MD Anderson Cancer Center offers excellent benefits, including medical, dental, paid time off, retirement, tuition benefits, educational opportunities, and individual and team recognition.
This position may be responsible for maintaining the security and integrity of critical infrastructure, as defined in Section 113.001(2) of the Texas Business and Commerce Code and therefore may require routine reviews and screening. The ability to satisfy and maintain all requirements necessary to ensure the continued security and integrity of such infrastructure is a condition of hire and continued employment.
It is the policy of The University of Texas MD Anderson Cancer Center to provide equal employment opportunity without regard to race, color, religion, age, national origin, sex, gender, sexual orientation, gender identity/expression, disability, protected veteran status, genetic information, or any other basis protected by institutional policy or by federal, state, or local laws unless such distinction is required by law.http://www.mdanderson.org/about-us/legal-and-policy/legal-statements/eeo-affirmative-action.html

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