Title: Research Data Scientist
Location: Onsite, Pittsburgh, PA 15213 Type: Contract to Hire Hours: Standard business hours Overview: Join a cutting-edge lab to discover novel therapeutics who are seeking a Research Data Scientist to provide advanced analytical and computational support for multidisciplinary biomedical research. This role will develop data pipelines, statistical models, and AI/machine learning approaches to analyze and integrate complex biological datasets, including multi-OMICs, imaging, virology, and other multimodal data. Responsibilities:- Develop scalable, reproducible data analysis pipelines for complex biological datasets.
- Apply statistical modeling, machine learning, and AI for predictive analytics and pattern recognition.
- Integrate and analyze multi-OMICs, imaging, molecular, cellular, and other multimodal data.
- Partner with investigators on study design, data strategy, and analytical approaches.
- Maintain data quality, preprocessing, version control, and standardized workflows.
- Create visualizations, dashboards, reports, and analytical summaries.
- Support data infrastructure and collaborate across biology, engineering, and computational teams.
Requirements:
- Master’s degree in Bioinformatics, Biostatistics, Computational Biology, Data Science, Statistics, Computer Science, or related field; Ph.D. preferred.
- 3+ years of relevant data analysis, statistical modeling, or computational research experience.
- Strong proficiency in Python and/or R and statistical analysis.
- Experience with large, complex datasets and reproducible computational pipelines.
- Strong analytical, problem-solving, communication, and collaboration skills.
Preferred Qualifications:
- Experience with multi-OMICs integration, machine learning/AI, advanced modeling, or quantitative imaging.
- Familiarity with cloud/HPC/big-data environments and data visualization.
- Biomedical or translational research experience.
- Experience contributing to scientific publications, grants, technical reports, or regulatory-aligned data frameworks.
#M3 #LI-KM2 Ref: #558-Scientific 
