Data Engineering Graduate Scholar

Job Listing No: 9740000

Data Engineering Graduate Scholar

Bayer is a global enterprise with core competencies in the Life Science fields of health care and agriculture. Its products and services are designed to benefit people and improve their quality of life. At Bayer you have the opportunity to be part of a culture where we value the passion of our employees to innovate and give them the power to change.
Data Engineering Graduate Scholar
YOUR TASKS AND RESPONSIBLITIES
The primary responsibilities of this role, Data Engineering Graduate Scholar, are to:
Design and develop pipelines to connect external data sources to a data lake in a collaborative effort with Bayer R&D IT and Bayer Biologics;
Provide analysis and feedback about experimental results to supervisors, highlighting important results, and defining next step experiments;
Design and develop workflows to link datasets in the data lake based on shared ontologies;
Gain expertise in frameworks for schema discovery from schema-free sources and use expertise gained to extract knowledge from existing schema-free sources;
Apply machine learning and statistical techniques to large multivariate datasets to identify relationships between variables;
Collaborate with data scientists and scientific stakeholders to apply appropriate analytical techniques and effectively communicate the results of analyses;
Develop assays and other experimental techniques that characterize innovative technologies, and promote to further development efforts for projects and late-stage projects;
Demonstrate knowledge of specialized laboratory and scientific techniques relative to area of expertise. Responsible for lab equipment specific to research expertise, including maintenance and assigned lab areas;
Coordinate and cooperate on research activities with peers, supervisors, and subordinates;
Communicate effectively by listening, documentation, and presentation;
Broad understanding of instrumentation and scientific principles;
Works with external service providers or outsourcing providers.
WHO YOU ARE
Your success will be driven by your demonstration of our LIFE values. More specifically related to this position, Bayer seeks an incumbent who possesses the following:
Required Qualifications:
Ph.D. with no relevant experience or Masters degree in field of expertise, plus a minimum of 1 year equivalent experience in Computer Science, Chemistry, Statistics, Mathematics, Bioinformatics, or a related field;
Experience in Machine Learning or Natural Language Processing;
Experience with a scripting language (python, POSIX shell, etc.);
Experience with a systems programming language (go, haskell, C, java, groovy, etc.);
Basic understanding of diverse spectroscopic techniques such as UV, IR, Raman and Mass Spectrometry;
At least one semester education (or equivalent knowledge acquired through experience) in Analytical Chemistry or structure elucidation of organic molecules;
Research experience in field of expertise with a broad understanding of scientific principles;
Ability to conceptualize, design, and execute experiments that address research questions;
Proficiency with experimental design, statistical analysis, and scientific instrumentation;
Excellent interpersonal, communication, and presentation skills. *Domestic relocation may be available.
YOUR APPLICATION
Bayer offers a wide variety of competitive compensation and benefits programs. If you meet the requirements of this unique opportunity, and you have the “Passion to Innovate” and the “Power to Change”, we encourage you to apply now. 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.
Location:
Division:
Crop Science
Reference Code:
26826
Contact Us
+ 1 888-473-1001, option #5

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