Director/Sr. Director Translational Data Sciences

Zentalis develops small molecule therapeutics with differentiated product profiles for a broad range of cancers.

SUMMARY:

Assist in the building of the bioinformatics team and implementing computational biology and biological data science strategy, across the organization in both a technical and leadership capacity, making a significant impact in both Discovery and Translational research.

RESPONSIBILITIES:

• Lead the development of computational methods for integrative analysis and visualization of large multi-omics datasets, such as RNA-seq, WES, WGS, chromatin profiling, at bulk and single cell sequencing level, proteomics and metabolomics, and correlation with clinical and translational data
• Lead the development of statistical and/or machine learning models that interrogate large datasets, either molecular, biological or clinical, to validate hypothesis and support therapeutic, clinical or biomarker development
• Collaborate with interdisciplinary teams to drive biological data stewardship efforts, data analysis, integration, and use across multiple sources, platform and projects
• Partner with key stakeholders across the organization to set and implement translational data analysis strategy.
• Translate insight from model systems into predictors and classifiers of therapeutic response, therapeutic index and prognosis in clinical diseases.
• Foster innovation and new product development using state of the art data science - machine learning and artificial intelligence.
• Coordinate a team to produce high quality and detailed documentation for all projects, setting a standard of high-performance and quality.
• Maintain high-functioning and synergistic relationships across the Company’s data-driven clinical departments, including Clinical Development, Biostatistics and Data Management, to drive or contribute to clinical studies’ exploratory analysis.
• Communicate science and strategy effectively in a variety of internal and external settings.
• Participate in competitive intelligence, as well as scientific and clinical knowledge management, to track advances in relevant therapeutic and technical areas, by interacting with external experts, attending scientific meetings, and staying abreast of the literature.
• Further the Company’s culture of scientific excellence and achievement as well as champions the career growth of a talented team of cancer biologists.

REQUIREMENTS:

• PhD in bioinformatics, statistics, bioengineering, quantitative genetics or molecular biology applied to cancer research with 8+ years of industry experience and strong publication record in peer-reviewed journals.
• Deep knowledge and hands on experience of using publicly available pre-clinical and translational cancer biology data repositories and resources (e.g. DepMap, Human Protein Atlas, CTD2, TCGA or AACR project GENIE).
• Proficient in R or Python; comfortable with basic operation and maintenance of a Linux environment; Familiar with good coding and software development practices
• Proven record developing strategic vision leveraging data analysis, including machine learning approaches, to alter the paradigm for target and biomarker discovery in support of drug discovery and clinical development projects.
• A track record of publications demonstrating technical or scientific leadership in innovative projects involving analysis and functional interpretation of large genomics or multi-omics data sets
• Experience in team management or leading team-driven projects in data analysis; Proven ability to mentor and develop world class talent.
• Excellent leadership capabilities with demonstrated skills in building, guiding, and motivating effective teams and fostering productive research collaborations.
• Preferred experience working with patient-derived, clinical or medical record data in the context of retrospective, registry or trial studies in oncology.
• Preferred familiarity with cloud-computing environments
• Preferred affinity for the practice of unbiased, hypothesis-generating analysis and general data exploration using innovative and creative computational approaches and visualizations.
• Record of successfully working cooperatively in a matrix type organization.
• Strong interpersonal and communication skills, experience working with multi-disciplinary teams and leading projects
• Strong technical and scientific writing skills.