Data Scientist Quantitative Genetics Biology Intern

Key Skills

Cloud computing, Python Programming, SQL

Job Description

The primary responsibilities of this role, Data Scientist Quantitative Genetics Biology Intern, are to:

• Build and validate predictive models incorporating key breeding data, soil, weather, and environmental data;
• Demonstrate the application of the models and deploy them to stakeholders;
• Contribute to positive team culture and work ethos based on Bayer LIFE values;
• Support the Health, Safety, and Environment, Compliance, Business Conduct, and Human Rights policies and culture.

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:

• Currently enrolled at the University of Illinois-Champaign Urbana pursuing an advanced degree Master of Science or Ph.D. student in Computational Biology, Genetics, Bioinformatics or similar field with focus in Computer Science, Statistics, Data Science, Mathematics or similar field;
• Strong programming skills in R, Python, SQL, Java or Linux;
• Data-driven methods for target identification and biomarker discovery;
• Problem solving ability and experience in analyzing and presenting complex data;
• Utilizing public datasets on bulk and single-cell RNA-seq for target and biomarker discovery;
• Implementing computational tools for variant impact prediction;
• Using bioinformatics techniques for mutation assessment and target prioritization;
• Organizational, interpersonal, and written communication skills;
• Strong business aptitude, the ability to rapidly learn new problem domains, and become conversant in the domain with subject matter experts;
• Ability to communicate complex ideas in a clear, precise and actionable manner;
• Detail and results oriented with the ability to work independently;
• Ability to actively engage with internal partners and external collaborators to align strategies and success measures in analytics;
• Able to work 10-20 hours per week if interning during the semester;
• Able to work 40 hours per week if interning during the summer.

Preferred Qualifications:

• Experience with cloud computing such as Hadoop and Spark;
• Performing machine-learning/deep-learning with focus on multi-omics data integration.