Computational Scientist II at Takeda in Boston, MA

OBJECTIVES/PURPOSE

• Support translational bioinformatics needs for key oncology clinical projects, including high-throughput data QC, process, analysis and integration.
• Integrate and analyze pre-clinical and clinical, internal and public domain datasets, to generate and evaluate hypotheses for drug combination, new disease indications, and mechanism of action purposes.
• Apply state-of-the-art AI/ML methods for clinical biomarker identification and validation.
• Drive collaborations with internal groups, external partners, including CROs and academia for data analysis and machine learning.

ACCOUNTABILITIES

• Support oncology clinical science and translational research teams to achieve translational research and clinical objectives using advanced computational biology techniques.
• Interact closely with biologists and clinicians to conduct analyses, data integration and data interpretation.
• Identify, build, and use bioinformatic pipelines to process and QC omics data types including genomics, transcriptomics, single cell sequencing, proteomics and metabolomics.
• Interpret preclinical and clinical datasets using appropriate computational and statistical methods.
• Create visualizations, interpret high dimensional data and explain results to cross-functional teams.
• Schedule and execute on tasks to meet deadlines.
• Plan and coordinate computational biology activities internally and in partnership with external CROs and academic partners, including complex projects requiring multiple members of the team and organization.
• Prepare and present comprehensive scientific reports to a full range of internal and external audiences.
• Work collaboratively with data scientists and data engineering groups to enhance our computational infrastructure, user interface, query and visualization capabilities.
• Writes study reports and presents data effectively in all settings and with participants of all levels of the organization.

DIMENSIONS AND ASPECTS

• Strong background with high dimensional data analysis derived from Next Generation Sequencing, including some of the following: RNASeq, DNASeq, , epigenetics, and single cell sequencing.
• Knowledge of and experience with machine learning and bioinformatic techniques.
• Hands-on experience developing and implementing bioinformatic pipelines for data analysis on RNASeq, DNASeq, single cell datasets, and metabolomics data.
• Solid knowledge of Unix/Linux, command line interfaces, and fluency in some common scripting and/or programming language (e.g., R, Python, Perl, Java, C / C++).
• Familiarity with parallel computing, relational databases (e.g., SQL) and cloud computing or distributed computing (i.e. AWS)
• Theoretical knowledge of bioinformatics, computational biology; keeps current with emerging trends in bioinformatics and computational biology
• Familiarity with popular public domain data sources and programmatic interfaces
• Experience in designing and conducting computational biology activities to meet program objectives; able to provide input on timelines and resource needs as indicated
• Able to evaluate/develop computational methods based on project needs
• Basic knowledge of biomedical science and technologies outside specific discipline
• Strong scientific understanding of molecular biology and genomics
• Excellent problem solving, communication, presentation, and interpersonal skills
• Independent, self-starting and supportive of team-based research and able to work effectively in a matrix organization

Leadership

• Ability to work in a team and influence team to make data driven decisions

Decision-making and Autonomy

• Independently manages own workload
• Scientifically independent
• Ability to search literature and come up with innovative solution to difficult problems

Interaction

• Conducts scientific presentations to internal audiences

Innovation

• Receives high level instructions on all work, determines methods on new assignments, works closely with manager, may manage junior staff
• Determines methods on new assignments; perform literature search as needed to propose innovation solutions

EDUCATION, BEHAVIOURAL COMPETENCIES AND SKILLS:

• PhD degree in a scientific discipline, with 4+ years experience, or
• MS with 8+ years experience, or