Data Scientist II - Quantitative Biology, Multi-OMICs Integration, and AI/ML Modeling

The University of Pittsburgh; Pittsburgh (Allegheny County); On-site; USD 90,000 - 130,000; Full time

Job summary

The University of Pittsburgh invites applications for a Data Scientist II in Quantitative Biology, focusing on multi-OMICs integration and AI/ML modeling in a translational research setting.

The role emphasizes development of scalable data analysis pipelines, statistical modeling, and collaborative work across biology, engineering, and computational sciences. A Master's degree is required (PhD preferred) with at least 3 years of relevant experience.

Qualifications

• Master’s degree (Ph.D. preferred) in a quantitative field such as Bioinformatics, Biostatistics, Computational Biology, Data Science.
• Minimum of 3 years of relevant experience in data analysis, statistical modeling, or computational biology.
• Strong expertise in statistical analysis, quantitative modeling, and data interpretation.
• Proficiency in programming languages commonly used in scientific computing (Python, R).
• Experience working with complex, high-dimensional biological datasets.
• Experience developing reproducible computational workflows and data processing pipelines.

Responsibilities

• Design and implement robust, scalable data analysis pipelines for multimodal datasets (virology, imaging, multi-OMICs).
• Lead development and application of statistical models to quantify infection dynamics and therapeutic endpoints.
• Develop and apply machine learning and AI-based approaches for pattern recognition and predictive modelling.
• Perform integrative, systems-level analyses across diverse molecular, cellular, functional, and temporal datasets.
• Collaborate with investigators on study design, statistical planning, and quantitative frameworks.

Skills

Statistical analysis

Data interpretation

Communication skills

Independent & collaborative

Education

Master’s degree (Ph.D. preferred) in Bioinformatics, Biostatistics, Computational Biology, Data Science

Tools

Python

R

Machine learning

Job description

Job Description - Data Scientist II - Quantitative Biology, Multi-OMICs Integration, and AI/ML Modeling (26006440)

Data Scientist II - Quantitative Biology, Multi-OMICs Integration, and AI/ML Modeling

Med-Medicine - Pennsylvania-Pittsburgh - ( 26006440 )

The Pulmonary, Allergy, Critical Care, and Sleep Medicine Division is made of up approximately 70 clinical staff and over 100 research staff who work in a variety of locations including: Bridgeside Point, Biomedical Science Tower (BST), UPMC Hospitals including Presbyterian, Shadyside, East, Jameson and Mercy. The division provides world class services across 10 inpatient services at five hospitals and over 70,000 outpatient office visits. We have a major research mission that focuses on basic, clinical, and translational research on the lung, microbiome, COVID-19, sleep medicine, and allergy and immunology.

The Benam Lab (https://www.benamlab.net/) at the University of Pittsburgh Departments of Medicine and Bioengineering is seeking a highly motivated Data Scientist II to provide advanced analytical and computational expertise for a multidisciplinary research program focused on human-relevant experimental systems (microphysiological systems; Organs-on-Chips). This role will lead the development and implementation of data analysis pipelines, statistical modeling frameworks, and machine learning approaches to enable integration and interpretation of complex biological datasets.

The position will support high-dimensional data analysis across virology, imaging, and multi-OMICs platforms, and will contribute to development of standardized, regulatory-aligned data frameworks to support predictive modeling and translational decision-making.

Required Qualifications

• Master’s degree (Ph.D. preferred) in Bioinformatics, Biostatistics, Computational Biology, Data Science, or a related quantitative field
• Minimum of 3 years of relevant experience in data analysis, statistical modeling, or computational biology (or equivalent combination of education and experience)
• Strong expertise in statistical analysis, quantitative modeling, and data interpretation
• Proficiency in programming languages commonly used in scientific computing (e.g., Python, R)
• Demonstrated experience working with complex, high-dimensional biological datasets
• Experience developing reproducible computational workflows and data processing pipelines
• Strong analytical, problem-solving, and communication skills
• Ability to work independently and collaboratively in multidisciplinary environments

Preferred Qualifications

• Ph.D. in a relevant quantitative or computational discipline
• Experience with multi-OMICs data integration (e.g., transcriptomics, proteomics, metabolomics)
• Experience with machine learning, deep learning, or data-driven modeling approaches in biomedical research
• Familiarity with image analysis workflows and quantitative imaging data
• Experience with systems biology approaches and integrative modeling
• Experience developing or supporting regulatory-aligned data frameworks or standardized data pipelines
• Experience contributing to scientific publications, grant proposals, or regulatory submissions
• Experience working in multidisciplinary teams integrating computational and experimental research

Job Summary

Performs research, analysis, and modeling on organizational data and data sets utilizing advanced statistical methods to mine and analyze complex and unstructured data sets. Offers complex analysis and utilizes advanced algorithms and statistical software. Adheres to all protocols.

Essential Functions

• Design and implement robust, scalable data analysis pipelines for multimodal datasets, including virology, imaging, and multi-OMICs data
• Lead development and application of statistical models to quantify infection dynamics and therapeutic response endpoints
• Develop and apply machine learning and AI-based approaches for pattern recognition, predictive modelling, and target discovery
• Perform integrative, systems-level analyses across diverse data types (molecular, cellular, functional, and temporal datasets)
• Collaborate with investigators on study design, statistical planning, and development of quantitative frameworks for experimental studies
• Establish and maintain reproducible computational workflows, including data preprocessing, quality control, and version‑controlled pipelines
• Develop data standards, organization strategies, and reporting structures aligned with regulatory expectations (e.g., ISTAND‑ready frameworks)
• Generate high‑quality data visualisations, analytical reports, and summaries to support internal decision‑making and external dissemination
• Contribute to preparation of manuscripts, grant applications, and technical reports
• Support development and maintenance of data infrastructure to enable efficient data storage, access, and analysis
• Collaborate closely with multidisciplinary teams spanning biology, engineering, and computational sciences

Physical Effort

Must be able to work on a computer for prolonged periods of time.

The University of Pittsburgh is an equal opportunity employer / disability / veteran.

Assignment Category Full‑time regular

Job Classification Staff.Data Scientist II

Job Family Research

Job Sub‑Family Data Science

Campus Pittsburgh

Minimum Education Level Required Master's Degree

Minimum Years of Experience Required 3

Will this position accept substitution in lieu of education or experience? Combination of education and relevant experience will be considered in lieu of education and/ or experience requirement.

Work Schedule Monday - Friday; 8:30am - 5pm

Work Arrangement On-Campus: Teams that work on campus, in an office, or in a lab.

Hiring Range TBD Based Upon Qualifications

Relocation Offered No

Visa Sponsorship Provided Yes

Background Check For position finalists, employment with the University will require successful completion of a background check

Child Protection Clearances Not Applicable

The University of Pittsburgh is an equal opportunity employer / disability / veteran.