Director, Data Science, Functional Genomics

Location: Cambridge, Massachusetts, United States; hybrid work arrangement; US and Puerto Rico residents only; no relocation

Base salary: $214,100–$337,000 per year, plus annual bonus and long-term incentive eligibility where applicable.

Company

hirify.global is a global, research-intensive biopharmaceutical company developing small-molecule and biologic therapies.

What you will do

• Lead the design and development of scalable computational analytics for pooled, arrayed, single-cell, and optical CRISPR screens, including QC, library design, and longitudinal readout analysis.
• Develop functional genomics methods involving single-cell perturbation screening, cellular barcoding, lineage tracing, resistance mechanisms, and drug combinations.
• Build image-analysis pipelines for high-content and optical CRISPR screens and connect morphological phenotypes to target prioritization.
• Integrate functional genomics, imaging, transcriptomics, and proteomics data into multi-evidence target prioritization packages.
• Apply AI, ML, LLM-powered agentic workflows, and network-based methods to triage targets and synthesize biological evidence.
• Build and lead a team of scientists, set technical strategy, establish reproducible research and FAIR data standards, and collaborate with experimental scientists, software engineers, and external partners.

Requirements

• Ph.D. in Bioinformatics, Biostatistics, Computational Biology, Statistics, Computer Science, Mathematics, or a related field.
• At least 10 years of relevant experience in computational biology, bioinformatics, biostatistics, or a related quantitative discipline, including hands-on analysis of large-scale NGS and functional genomics datasets.
• Experience leading and building analytics teams, setting technical strategy, and mentoring scientists.
• Experience with computational analysis, algorithm development, and biological interpretation of diverse large-scale NGS and functional genomics datasets.
• Proven experience applying machine learning to single-cell RNA sequencing data, plus experience with experimental design, statistical hypothesis testing, and multi-omics data integration.
• Proficiency in at least one statistical programming language, such as R or Python, and experience with Git-based version control.
• Familiarity with public repositories including The Cancer Genome Atlas, Dependency Map, Cancer Cell Line Encyclopedia, and Clinical Proteomic Tumor Analysis Consortium.
• Experience with AWS cloud infrastructure and Linux environments.
• Excellent oral and written communication skills.

Nice to have

• Post-doctoral or relevant industry experience, including leadership of multidisciplinary teams and influence on scientific strategy.
• Functional genomics experience, including CRISPR screen hit-calling frameworks and library design interpretation.
• Optical pooled CRISPR image-analysis pipelines and integration of morphological readouts with genomic datasets.
• Deep learning for image-based phenotypic profiling and cell classification.
• Knowledge of disease biology, immunology, and current functional genomics research.
• Network-based analysis or transfer learning for inferring gene regulatory patterns from NGS datasets.
• Experience building or deploying LLM-powered systems or AI tools for biological data interrogation.
• Interactive multi-omics visualization tools such as R Shiny, and novel functional genomics methods demonstrated through first-author publications or released tools.

Culture & Benefits

• Hybrid work arrangement with up to 10% travel required.
• Regular employee status with medical, dental, vision, insurance, retirement benefits including 401(k), paid holidays, vacation, and sick and compassionate leave.
• Inclusive research environment focused on interdisciplinary collaboration and breakthrough biopharmaceutical science.
• Visa sponsorship is not available, and relocation is not provided.