Director, Computational Biology
Ikena Oncology is a targeted oncology company focused on developing cancer therapies targeting key signaling pathways that drive the formation and spread of cancer. Ikena is advancing five programs that include four product candidates in either clinical development or IND-enabling studies. Ikena has entered into a global strategic collaboration with Bristol-Myers Squibb Company for its IK-175 and IK-412 programs.
Ikena Oncology is seeking a highly talented, diversely experienced, and self-motivated computational biology leader to join an innovative, scientifically driven and fast paced team focused on developing breakthrough cancer therapies. The Director of Computational Biology will play an impactful role in the development and execution of an innovative computational biology strategy by working closely with discovery, translational research and clinical development, and providing hands-on computational support for data analysis, management and reporting need.
- Establish relationship and effectively partner with other key functions including discovery, translational research and clinical development to roadmap, structure, prioritize and execute on a variety of computational analyses to address critical biological and clinical questions
- Evaluate and make recommendation on accessing public / private genomic data sets to inform Ikena research and clinical development activities
- Integrate and analyze multi-omics data from proprietary and publicly available datasets via genome-scale modeling or machine learning methodologies to support new target evaluation, biomarker discovery, indication selection and patient stratification
- Establish relationships with and oversee computational data analysis performed by external consultants
- Collaborate cross-functionally to optimize data management, standardize methods, and establish SOPs that maximize analysis capability and enhance efficiency
- Champion the design, build and maintenance of internal databases to organize multi-dimensional data from the pre-clinical and clinical studies
- Identify and lead the evaluation/implementation of novel tools, or develop customized solutions to meet analysis, data visualization/reporting need, and proactively expand Ikena computation biology capabilities
- Communicate critical computational biology recommendations, activities and analysis results to key stakeholders including Executive Team, functional heads and program teams
- Develop future human and computational resourcing plans in alignment with corporate, programmatic, and functional objectives
- Ph.D. in computational biology, bioinformatics, or data science related fields with 10+ years of experience in the biotech or pharmaceutical industry
- Deep knowledge of public genomic, transcriptomic databases, and common bioinformatics tools for data analysis to support discovery and translational studies
- Excellent data management and analytical skills. Ability to derive insights from complex multi-dimensional biological data including genomic, transcriptomic, single cell RNAseq, flow cytometry or IHC
- Solid understanding of the genetic and molecular mechanism of cancer
- Proficiency in scalable, cloud-based data processing implementations (AWS), including containerization, workflow management solutions, as well as data tidying and data storage best-practices
- Demonstrated expertise in at least one programming language (R, Python, Go, C++)
- Experience interfacing via APIs with multiple database types, including SQL and NoSQL
- Firm grasp of modern statistical methods and machine learning techniques, and their applications to large-scale, high throughput dataset analysis
- Established track record of driving initiatives to milestones
- Proven ability to use highly effective influencing skills to drive collaboration, achieving results, and resolving conflicts across function areas and project teams
- Excellent interpersonal and written / verbal communication skills
Personal attributes: team oriented, goal-driven, organized, highly collaborative, open-minded, data-driven, creative, persistent in the face of obstacles and uncertainty, flexible, self-aware of strengths and weaknesses, objective in the evaluation of data and strongly optimistic about overcoming challenges.