Genomics Data Scientist Single Cell Sequencing

Closed

Institution
Bayer
Location
Chesterfield, Missouri, USA
Salary Range
$103,000/yr - $154,000/yr USD

Description
As part of a collaboration project focused on single cell sequencing for agricultural biology, we are seeking a passionate and creative scientist to join the Crop Science Plant Biotechnology genomics team. This two-year position will be focused on cutting edge functional genomics analysis to generate insights into the genome biology of various eukaryotic systems. This genomics data scientist will be part of an interdisciplinary team with expertise in Cell Biology, Genomics, and Data Science to move forward specific high-impact projects for crop science.

The ideal candidate will be able to implement cloud-based genomics pipelines and improve and optimize them; be able to generate insights from genomic data on various eukaryotic systems; work well with cross-disciplinary and global teams; and be able to articulate findings and integrate his/her work into the established R&D teams.

Responsibilities

• Provide technical contributions in a fast-paced team environment to accelerate our efforts on building an analytics-driven product pipeline.
• Independently perform statistical analysis, computer programming, predictive modeling and experimental design.
• Build cross-functional relationships to collaboratively partner with the business and effectively network amongst diverse scientific disciplines within data science, genomics, and biotechnology-based communities.
• Contribute to the development of code, bioinformatic analyses pipelines, computational tools, and databases for mining and visualizing large genomic data sets.
• Develop sustainable, consumable, accurate, and impactful reporting on model inputs, model outputs, observed outputs, business impact, and key performance indicators.
• Present compelling, validated stories to all levels of organization, including peers, senior management, and internal customers to drive both strategic and operational changes in business.

Qualifications

• PhD in a relevant domain, including genomics, computational biology, molecular biology & genetics, etc.
• Educational preparation or applied experience in at least one of the following areas: Machine Learning, Statistical Genetics, Statistics, Biostatistics, Bioinformatics, Genomics, Computational Biology or other related quantitative discipline.
• Demonstrates intermediate proficiency in computational skills and level of experience analyzing large datasets and/or building data models using R, Python or other statistical and/or mathematical programming packages.
• Demonstrates basic understanding of software development best practices (Version Control, Code Documentation & Review, Cloud Based Sequence Analysis, Database Management).
• Intermediate proficiency in machine learning algorithms and concepts.
• Experience in successful delivery of valuable analysis through application of domain knowledge.
• Strong communication competencies including presentations and delivery of complex quantitative analyses in a clear, concise and actionable manner to extended team and small groups of key stakeholders.