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Bioinformatics Data Scientist Remote Jobs (NOW HIRING)

The Pennsylvania State University

Approval of remote and hybrid work is not guaranteed regardless of work location.For additional ... Lead data wrangling, harmonization, standardization, and quality control of existing biological ...

Elder Research

Data Scientist (Remote)

Arlington, VA · On-site +1

Data Scientist Workplace: Washington DC Metro Area - Remote (candidates MUST BE located in the National Capital Region - DMV) Clearance Required: a TS or CBP BI or DHS Suitability clearance ...

Zenlaw

Data Scientist (Remote)

New York, NY · On-site +1

As a Data Scientist, you will be working with our engineering team to model complex problems and ... Due to the remote nature of this role, we are unable to provide visa sponsorship.

Elder Research

Data Scientist (Remote)

Arlington, VA · On-site +1

Data Scientist Workplace: Washington DC Metro Area - Remote (candidates MUST BE located in the National Capital Region - DMV) Clearance Required: a TS or CBP BI or DHS Suitability clearance ...

Victory

Data Scientist (Remote)

Austin, TX · Remote

About the Data Scientist position We are looking for a skilled Data Scientist who will help us analyze large amounts of raw information to find patterns and use them to optimize our performance. You ...

Inspira Financial

Data Scientist (Remote)

Oak Brook, IL · On-site +1

The Data Scientist will report to the Director, Data Science & Analytics in the CDB Strategy Department. This role is responsible for participating in team building business intelligence through the ...

New

Inspira Financial

Data Scientist (Remote)

Oak Brook, IL · Remote

The Data Scientist will report to the Director, Data Science & Analytics in the CDB Strategy Department. This role is responsible for participating in team building business intelligence through the ...

New

Futran Tech Solutions Pvt. Ltd.

Data Scientist

New Demand - Data Scientist Remote * Total Years of experience 10-12 years * 6 months+ * Occasional travel to the client location is required. * Candidates might need to overlap with offshore on need ...

Bruker Corporation

Scientist, Bioinformatics

The Bioinformatician will furthermore play a role in performing CellScape data analyses for key ... findings to scientists, researchers, and stakeholders through clear written reports and ...

GD Resources LLC

Data Scientist - Remote Role

Remote Position Summary The Senior Data Scientist provides advanced analytical expertise supporting the SBA OIG Technology Solutions Division through the design, development, deployment, and ...

New

UnitedHealth Group

Data Scientist - Remote

Minnetonka, MN · On-site +1

$112K - $193K/yr

The role partners closely with Data Scientists, Product Teams, and Platform Teams to deploy AI-driven intelligence across PI use cases * Contribute to experimentation with novel ML and Generative AI ...

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Bioinformatics Data Scientist Remote information

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How much do bioinformatics data scientist remote jobs pay per year?

As of Jul 14, 2026, the average yearly pay for bioinformatics data scientist remote 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.
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Bioinformatics Data Scientist Remote jobs near you
ML / Bioinformatics Data Scientist

ML / Bioinformatics Data Scientist

IT America Inc

Dallas, TX • Remote

Contractor

Re-posted 12 days ago

Job description

Position: ML / Bioinformatics Data Scientist

Location: Remote (PST work hours)

Duration: Long term contract

About the Role:

We are seeking a highly motivated and collaborative Bioinformatics/ML scientist to join the Computational biology & Medicine department in Computational Sciences COE (Center of Excellence) within Genentech’s Research and Early Development (gRED). The successful candidate will contribute to a cross-functional project that will apply Machine Learning (ML) models to multi-modal datasets collected from clinical trials. This role requires a deep understanding of application of Machine Learning models, a background in biology, a passion for innovation, and a commitment to improving healthcare outcomes through cutting-edge technology.

We are looking for exceptional researchers with a passion for interdisciplinary research and technical problem-solving, and a proven ability to develop and implement research ideas. The candidate is expected to have worked on previous ML modeling projects and applying them to multi-modal datasets to be considered.

About the Project:

The goal of this project is to develop a machine learning model to predict a patient's risk for drug-induced liver toxicity based on a wide variety of patient characteristics including clinical, genetics, omics and safety labs. The focus will be harmonizing these diverse data sources, deriving new features, and  building machine learning models designed to identify a predictive signature that can distinguish between at-risk and not-at-risk patient populations.

Key Responsibilities:

  • Data centralization and harmonization
  • Applying ML methods on assembled dataset to identify patients’ risk for drug-induced liver toxicity.
  • Collaborate with interdisciplinary and cross-functional teams including biologists, chemists, data scientists, and other stakeholders.

Educational Background:

  • PhD degree in quantitative field ( e.g., Computer Science, Computational Biology, Bioinformatics, Statistics, Mathematics) 

Experience:

  • Proven track record of working with statistical modeling techniques, including ML methods, is required
  • Demonstrated interest in problems across biology as applied to the discovery and development of treatments for disease is preferred

Technical Skills:

  • Data Science & Programming: Expertise in Python/R for data manipulation, statistical analysis, and ML model building (required)
  • Multimodal Data & Modeling: Proven ability to work with diverse data types (omics, clinical, imaging) (required).
  • Knowledge of statistics and experience with survival analysis (required)
  • Domain & AI-specific Skills: Experience with NLP/LLMs for feature extraction from unstructured text, and a strong background in a neuroscience (preferred)

Soft Skills:

  • Excellent communication, collaboration, and problem-solving skills (required).

Publications:

  • Strong publication record and experience contributing to research communities.