1

Freelance Bioinformatics Machine Learning Jobs in Secaucus, NJ

In addition, bioinformatics analysis of various types of patient genomic, epigenomic and ... machine learning • Prior experience working in CLIA environment is a plus • Experience in ...

PhD in computational biology, bioinformatics, machine learning, statistics, or a related field strongly preferred (we're open to exceptional MS candidates) * Genuinely strong in both machine learning ...

next page

Showing results 1-20

Freelance Bioinformatics Machine Learning information

See Secaucus, NJ salary details

$9

$31

$53

How much do freelance bioinformatics machine learning jobs pay per hour?

As of Sep 3, 2026, the average hourly pay for freelance bioinformatics machine learning in Secaucus, NJ is $31.77, according to ZipRecruiter salary data. Most workers in this role earn between $12.21 and $51.35 per hour, depending on experience, location, and employer.

What does a freelance bioinformatics machine learning specialist do?

A Freelance Bioinformatics Machine Learning specialist applies machine learning techniques to analyze biological data, such as genomics, proteomics, and medical records, on a project-by-project basis. They typically work independently with research labs, biotech companies, or healthcare organizations to develop algorithms, build predictive models, and interpret complex biological datasets. Their work helps drive insights in areas like drug discovery, personalized medicine, and disease prediction, often leveraging tools like Python, R, and specialized bioinformatics software. As freelancers, they have the flexibility to choose projects, set their schedules, and work remotely.

What are the key skills and qualifications needed to thrive as a freelance bioinformatics machine learning specialist?

To thrive as a Freelance Bioinformatics Machine Learning Specialist, you need a strong background in biology, statistics, and programming (such as Python or R), typically supported by a relevant degree in bioinformatics, computer science, or a related field. Familiarity with bioinformatics tools (e.g., BLAST, Bioconductor), machine learning libraries (scikit-learn, TensorFlow), and experience with cloud computing platforms are highly valuable. Strong problem-solving, communication, and project management skills help distinguish top freelancers in this field. These capabilities are crucial for independently delivering accurate, actionable biological insights to clients and efficiently managing multiple projects.

What are some common challenges freelance bioinformatics machine learning professionals face when working with multiple clients?

Freelance bioinformatics machine learning professionals often encounter challenges such as managing diverse data formats, aligning project expectations, and ensuring data privacy across multiple clients. Each client may have unique datasets, varying levels of documentation, and different computational infrastructure, requiring adaptability and strong communication skills. Balancing multiple deadlines and maintaining clear, consistent reporting are also important to foster trust and long-term collaborations.

What is the difference between Freelance Bioinformatics Machine Learning vs Freelance Data Scientist?

AspectFreelance Bioinformatics Machine LearningFreelance Data Scientist
CredentialsBackground in bioinformatics, biology, or related fields; knowledge of machine learningBackground in statistics, computer science, or related fields; strong programming skills
Work EnvironmentResearch labs, biotech companies, academic projects, freelance consultingVarious industries including finance, tech, healthcare, consulting
Industry UsagePrimarily biotech, healthcare, genomics, pharmaceutical sectorsBroad industry application including finance, marketing, tech, healthcare

Freelance Bioinformatics Machine Learning specialists focus on applying machine learning techniques to biological data, often working within biotech and healthcare sectors. In contrast, Freelance Data Scientists have a broader scope, working across multiple industries with diverse datasets. Both roles require strong analytical skills and programming expertise, but their industry focus and domain knowledge differ significantly.

What job categories do people searching Freelance Bioinformatics Machine Learning jobs in Secaucus, NJ look for?

The top searched job categories for Freelance Bioinformatics Machine Learning jobs in Secaucus, NJ are:

What cities near Secaucus, NJ are hiring for Freelance Bioinformatics Machine Learning jobs?

Cities near Secaucus, NJ with the most Freelance Bioinformatics Machine Learning job openings:

Bioinformatician III (Statistical Geneticist) - Windreich Department of AI & Human Health Research

Mount Sinai Hospital

Manhattan, NY • On-site

Full-time

Posted 15 days ago


Mount Sinai rating

7.7

Company rating: 7.7 out of 10

Based on 296 frontline employees who took The Breakroom Quiz

165th of 898 rated healthcare providers


Job description


We are seeking a highly motivated genetic epidemiologist/statistical geneticist to join a growing genomics and precision medicine research program at the Artificial Intelligence and Human Health Department as Bioinformatician III. The candidate will be working under the supervision of Dr. Nathalie Chami. The successful candidate will lead and support analyses of large-scale genomic, proteomic, multi-omics, and longitudinal clinical datasets, applying advanced statistical genetics, bioinformatics, machine learning, and AI approaches to uncover the biological basis of complex disease and rare disorders. This role offers the opportunity to drive independent research projects, contribute to high-impact publications and grants, and collaborate closely with a multidisciplinary team at the forefront of human genetics and precision medicine.
Responsibilities
  • Design and implement large-scale genetic analyses, including QC pipelines, GWAS, rare variant association analyses, PRS construction, fine-mapping, proteomics, and integrative genomics.
  • Develop reproducible computational pipelines for sequencing, association testing, multi-omics integration, and downstream biological interpretation.
  • Integrate multi-omics data, clinical, and imaging data to identify disease mechanisms, characterize disease heterogeneity, uncover risk factors, and prioritize therapeutic targets.
  • Conduct longitudinal analyses of clinical and genomic data, including time-to-event analyses, disease progression modeling, and trajectory analyses.
  • Apply machine learning and LLM-based approaches to large-scale genomic, multi-omics, imaging, and EHR data for gene discovery, disease subtyping, and precision medicine research.
  • Lead independent research projects and contribute to collaborative studies from conception through publication.
  • Contribute to study design, grant applications, manuscripts, presentations, and scientific reporting.
  • Mentor trainees and junior analysts and help establish best practices for data management, reproducibility, and computational workflows.
  • Collaborate closely with investigators, clinicians, and computational scientists across disciplines.
  • Other duties as assigned.

Qualifications
  • M.S. in Biological Sciences, Bioinformatics, Computer Sciences, Statistics or related discipline, PhD preferred.
  • Six years minimum experience required.
  • Working experience with genetics or statistics analysis software and online resources.

Preferred:
• Proficiency in R, Python, Unix/Linux, Bash scripting Git/GitHub, high-performance computing, and cloud computing environments.
• Strong experience with statistical genetics analysis workflows and tools including REGENIE, PLINK, SAIGE/SAIGE-GENE+, BOLT-LMM, GATK, bcftools/vcftools, FINEMAP/ SuSiE, coloc, PRSice/LDpred/PRS-CS etc.
• Hands-on experience analyzing large-scale genomic datasets (e.g., WES/WGS, UK Biobank, All of Us, etc.)., and proteomic datasets (e.g., Olink, SomaScan) and associated analysis frameworks.
• Proficiency in cloud computing environments (e.g. AWS, DNAnexus) and HPC clusters.
• Experience with workflow automation (e.g.WDL, Nextflow).
• Proficiency with generating and maintaining reproducible pipelines (Git/GitHub) and experience with machine learning, deep learning large language models (LLMs) and AI applications.
About Us
Strength through Unity and Inclusion
The Mount Sinai Health System is committed to fostering an environment where everyone can contribute to excellence. We share a common dedication to delivering outstanding patient care. When you join us, you become part of Mount Sinai's unparalleled legacy of achievement, education, and innovation as we work together to transform healthcare. We encourage all team members to actively participate in creating a culture that ensures fair access to opportunities, promotes inclusive practices, and supports the success of every individual.
At Mount Sinai, our leaders are committed to fostering a workplace where all employees feel valued, respected, and empowered to grow. We strive to create an environment where collaboration, fairness, and continuous learning drive positive change, improving the well-being of our staff, patients, and organization. Our leaders are expected to challenge outdated practices, promote a culture of respect, and work toward meaningful improvements that enhance patient care and workplace experiences. We are dedicated to building a supportive and welcoming environment where everyone has the opportunity to thrive and advance professionally. Explore this opportunity and be part of the next chapter in our history.
About the Mount Sinai Health System:
Mount Sinai Health System is one of the largest academic medical systems in the New York metro area, with more than 48,000 employees working across eight hospitals, more than 400 outpatient practices, more than 300 labs, a school of nursing, and a leading school of medicine and graduate education. Mount Sinai advances health for all people, everywhere, by taking on the most complex health care challenges of our time - discovering and applying new scientific learning and knowledge; developing safer, more effective treatments; educating the next generation of medical leaders and innovators; and supporting local communities by delivering high-quality care to all who need it. Through the integration of its hospitals, labs, and schools, Mount Sinai offers comprehensive health care solutions from birth through geriatrics, leveraging innovative approaches such as artificial intelligence and informatics while keeping patients' medical and emotional needs at the center of all treatment. The Health System includes more than 9,000 primary and specialty care physicians; 13 joint-venture outpatient surgery centers throughout the five boroughs of New York City, Westchester, Long Island, and Florida; and more than 30 affiliated community health centers. We are consistently ranked by U.S. News & World Report's Best Hospitals, receiving high "Honor Roll" status, and are highly ranked: No. 1 in Geriatrics, top 5 in Cardiology/Heart Surgery, and top 20 in Diabetes/Endocrinology, Gastroenterology/GI Surgery, Neurology/Neurosurgery, Orthopedics, Pulmonology/Lung Surgery, Rehabilitation, and Urology. New York Eye and Ear Infirmary of Mount Sinai is ranked No. 12 in Ophthalmology. U.S. News & World Report's "Best Children's Hospitals" ranks Mount Sinai Kravis Children's Hospital among the country's best in several pediatric specialties. The Icahn School of Medicine at Mount Sinai is ranked No. 11 nationwide in National Institutes of Health funding and in the 99th percentile in research dollars per investigator according to the Association of American Medical Colleges. Newsweek's "The World's Best Smart Hospitals" ranks The Mount Sinai Hospital as No. 1 in New York and in the top five globally, and Mount Sinai Morningside in the top 20 globally.
Equal Opportunity Employer
The Mount Sinai Health System is an equal opportunity employer, complying with all applicable federal civil rights laws. We do not discriminate, exclude, or treat individuals differently based on race, color, national origin, age, religion, disability, sex, sexual orientation, gender, veteran status, or any other characteristic protected by law. We are deeply committed to fostering an environment where all faculty, staff, students, trainees, patients, visitors, and the communities we serve feel respected and supported. Our goal is to create a healthcare and learning institution that actively works to remove barriers, address challenges, and promote fairness in all aspects of our organization.

What Mount Sinai employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom