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Remote Bioinformatics Machine Learning Jobs in Philadelphia, PA

Remote micro1 is engaging PhD-level Engineers in Electrical, Mechanical, or Chemical disciplines to ... Experience with or interest in AI, machine learning, or technology-driven projects (a plus, not ...

Remote micro1 is engaging PhD-level Engineers in Electrical, Mechanical, or Chemical disciplines to ... Experience with or interest in AI, machine learning, or technology-driven projects (a plus, not ...

Azure Data Architect

Malvern, PA · Remote

$65 - $84.75/hr

Remote Duration: Long Term Contract Visa- Only US Citizen, H4 EAD, L2S, TN Visa Experience: 12 to ... Experience in creating Data warehouse, data lakes for Reporting, AI and Machine Learning

Senior Data Analyst

Titusville, NJ · On-site +1

$110K - $117K/yr

Employer will accept a Master's degree in Statistics, Computer Science, Machine Learning & Data Science, Computational Informatics, Bioinformatics or related field and 1 year of experience in job ...

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Remote Bioinformatics Machine Learning information

See Philadelphia, PA salary details

$60K

$95.3K

$150.9K

How much do remote bioinformatics machine learning jobs pay per year?

As of Jun 28, 2026, the average yearly pay for remote bioinformatics machine learning in Philadelphia, PA is $95,333.00, according to ZipRecruiter salary data. Most workers in this role earn between $68,100.00 and $130,700.00 per year, depending on experience, location, and employer.

How do remote bioinformatics machine learning professionals typically collaborate with cross-functional teams?

Remote bioinformatics machine learning professionals often work closely with biologists, data scientists, and software engineers. Collaboration is typically facilitated through virtual meetings, shared code repositories, and project management tools. Regular communication is essential to align on data requirements, model development, and interpretation of results. While remote work offers flexibility, it requires strong organizational skills and proactive engagement to ensure seamless teamwork and project success.

What is a Remote Bioinformatics Machine Learning specialist?

A Remote Bioinformatics Machine Learning specialist is a professional who applies machine learning techniques to biological data, such as genomics or proteomics, while working from a remote location. They analyze complex biological datasets to uncover patterns, make predictions, and contribute to advancements in areas like drug discovery, disease research, and personalized medicine. These specialists typically have strong skills in programming, statistics, biology, and data analysis, and collaborate with researchers and healthcare professionals through digital communication tools.

What are the key skills and qualifications needed to thrive as a Remote Bioinformatics Machine Learning Specialist, and why are they important?

To excel as a Remote Bioinformatics Machine Learning Specialist, a strong background in computational biology, statistics, and machine learning—often supported by an advanced degree in bioinformatics, computer science, or a related field—is essential. Proficiency with programming languages like Python or R, experience using machine learning frameworks (such as TensorFlow or scikit-learn), and familiarity with bioinformatics tools and databases are typically required. Excellent problem-solving, self-motivation, and clear communication skills help professionals collaborate effectively and independently in remote environments. These abilities are vital for developing accurate models, interpreting complex biological data, and contributing meaningful insights to scientific research.

What is the difference between Remote Bioinformatics Machine Learning vs Remote Computational Biologist?

AspectRemote Bioinformatics Machine LearningRemote Computational Biologist
Required CredentialsMaster's or PhD in Bioinformatics, Computer Science, or related fields; experience in machine learningMaster's or PhD in Biology, Bioinformatics, or related fields; strong computational skills
Work EnvironmentRemote, collaborative teams in biotech, pharma, or research institutionsRemote or on-site, working in research labs or academic settings
Industry UsageUsed in biotech, healthcare, and pharmaceutical industries for data analysis and model developmentCommon in academic research, biotech, and healthcare for biological data interpretation

Remote Bioinformatics Machine Learning focuses on developing algorithms and models to analyze biological data using machine learning techniques. In contrast, Remote Computational Biologist applies computational methods to biological research questions, often integrating diverse data types. Both roles require strong computational skills and often overlap, but the former emphasizes machine learning expertise, while the latter has a broader biological research scope.

What are the most commonly searched types of Bioinformatics Machine Learning jobs in Philadelphia, PA? The most popular types of Bioinformatics Machine Learning jobs in Philadelphia, PA are:
What are popular job titles related to Remote Bioinformatics Machine Learning jobs in Philadelphia, PA? For Remote Bioinformatics Machine Learning jobs in Philadelphia, PA, the most frequently searched job titles are:
What job categories do people searching Remote Bioinformatics Machine Learning jobs in Philadelphia, PA look for? The top searched job categories for Remote Bioinformatics Machine Learning jobs in Philadelphia, PA are:
What cities near Philadelphia, PA are hiring for Remote Bioinformatics Machine Learning jobs? Cities near Philadelphia, PA with the most Remote Bioinformatics Machine Learning job openings:

Enterprise Solutions Graph Database

H R PUNDITS INC

Collegeville, PA • On-site, Remote

Full-time

Posted 26 days ago


Job description

Job title : Enterprise Solutions Graph Database/ Architect
Location: Upper Providence Township, PA
(Onsite/Remote )
Experience : 15 Years
Role Overview
Seeking a seasoned Graph Database
Knowledge Graph Expert to perform a comprehensive study of our existing platform. Evaluate our current architecture, data ontology, and query performance to provide a strategic roadmap. The goal is to evolve our Knowledge Graph into a robust, scalable engine that accelerates different Pharma areas ( drug discovery, clinical insights, and cross-departmental data democratization)
Required Qualifications
Graph Expertise: 10+ years of experience with Graph Databases. Deep proficiency in LPG (Labeled Property Graphs) or RDF/Triple Stores.
Pharma Domain Knowledge: Proven experience handling biomedical data types (e.g., Gene-Disease associations, Chemical compounds, Patient journeys).
Semantic Web Standards: Strong understanding of Linked Data principles, URI strategies, and ontology modeling.
Data Engineering: Experience with ETL/ELT pipelines that feed graphs from unstructured (PDF publications) and structured (EDC, LIMS) sources.
Advanced Analytics: Experience implementing Graph Data Science algorithms (centrality, community detection) or integrating Graphs with Machine Learning.
Technical Stack Preferences
Graph DBs: AnzoGraph, Neo4j, Stardog,
Languages: Python, Java, SPARQL, Cypher, or Gremlin.
Bio-Ontologies: Familiarity with OBO Foundry, ChEMBL, or Ensembl.