Bayer

Genomics Data Scientist (Crop Science - Vegetable ...

Job description

At Bayer we’re visionaries, driven to solve the world’s toughest challenges and striving for a world where 'Health for all Hunger for none’ is no longer a dream, but a real possibility. We’re doing it with energy, curiosity and sheer dedication, always learning from unique perspectives of those around us, expanding our thinking, growing our capabilities and redefining ‘impossible’. There are so many reasons to join us. If you’re hungry to build a varied and meaningful career in a community of brilliant and diverse minds to make a real difference, there’s only one choice.


Genomics Data Scientist (Crop Science - Vegetable R&D)


Collaborate with breeders and scientists in every major global region to develop cutting-edge, new genomic technologies to support transformation to the most advanced, quantitative vegetable breeding engine in the industry. Design and lead experiments in vegetable genotyping while contributing to meeting the genotyping needs of stakeholders across the vegetable R&D organization. Unique opportunity to work with all kinds of diversity – people, teams, regions, crops, and genetic populations. Leverage your genomics experience in 19 different crops! Explore professional and personal development opportunities tailored to your career goals and participate in domestic and international travel opportunities. Seeking a creative and passionate Genomics Data Scientist to join the Vegetable Seeds R&D Global Genomics team.


Your Tasks And Responsibilities


The primary responsibilities of this role, Genomics Data Scientist (Crop Science – Vegetable Seeds R&D), are:


  • Contributes to the development of new genomic resources for vegetable crops, including new high density genotyping platforms, new Genotyping By Sequencing (GBS) platforms, new skim sequencing platforms, whole genome sequencing projects, reference assembly sequencing projects, consensus genetic maps, and pangenomes;
  • Performs marker discovery, variant calling and filtering, marker picking, and genomic resource validation in the process of contributing to new genomic resource development;
  • Contributes to discovery efforts to develop heterotic pools across different vegetable breeding programs and develops automated workflows for population structure analysis across vegetable R&D;
  • Contributes to the development of automated digital analysis workflows;
  • Develops and maintains partnerships with scientists across organizations including Plant Biotechnology, Data Science & Analytics, and IT;
  • Identifies opportunities for new Proof of Concept (POC) experiments in new genomic and closely related technologies in new crops and works with internal and external collaborators to explore these POCs.


Who You Are


Your success will be driven by your demonstration of our LIFE (Leadership Integrity Flexibility Efficiency) values . More specifically related to this position, Bayer seeks an incumbent who possesses the following:


Required Qualifications:


  • PhD OR Master’s degree in Genomics, Plant Genetics, Data Science, Computational Genetics, Bioinformatics or related discipline;
  • Educational preparation or applied experience in Genomics;
  • Ability to code proficiently in R or Python;
  • Strong communication skills to include experience giving presentations and delivering complex quantitative analyses in a clear, concise, and actionable manner;
  • Ability to travel independently both domestically and globally including overnights up to 5%.


Preferred Qualifications:


  • Five or more years of relevant experience (to include industrial or academic experience post-undergraduate);
  • Prior experience in Plant Genetics, Computational Biology, Statistical Genetics, Bioinformatics or other related quantitative discipline;
  • Four or more years of research experience in Plant Genetics and Genomics;
  • Prior experience developing genotyping platforms and/or resources;
  • Experience with genetic population structure analysis.
  • Experience coding in R and/or Python;
  • Computational skills and experience analyzing genomics datasets using R or Python or other statistical and/or mathematical programming packages;
  • Prior experience running bioinformatics pipelines and using computational tools and databases for mining and visualizing large genomic datasets;
  • Prior experience with Breeding programs or partnering with plant breeders.


Position will be located in St. Louis, Missouri, Woodland, California, other approved US Bayer Crop Science site, or residence-based.


Domestic relocation may be available for this role.


Visa Sponsorship may be available for this role.


Employees can expect to be paid a salary between $103,000 to $140,000. Additional compensation may include a bonus or commission (if relevant). Additional benefits include health care, vision, dental, retirement, PTO, sick leave, etc. This salary (or salary range) is merely an estimate and may vary based on an applicant’s location, market data/ranges, an applicant’s skills and prior relevant experience, certain degrees and certifications, and other relevant factors.


YOUR APPLICATION


Bayer offers a wide variety of competitive compensation and benefits programs. If you meet the requirements of this unique opportunity, and want to impact our mission Science for a better life, we encourage you to apply now. Be part of something bigger. Be you. Be Bayer.


To all recruitment agencies: Bayer does not accept unsolicited third party resumes.


Bayer is an Equal Opportunity Employer/Disabled/Veterans


Bayer is committed to providing access and reasonable accommodations in its application process for individuals with disabilities and encourages applicants with disabilities to request any needed accommodation(s) using the contact information below.


Bayer is an E-Verify Employer.


Location: United States : Missouri : Chesterfield || United States : California : Woodland || United States : Missouri : St. Louis


Division: Crop Science


Reference Code: 801278


Contact Us


Email: hrop_usa@bayer.com


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