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.
YOUR TASKS AND RESPONSIBILITIES
The primary responsibilities of this role, Data Scientist, are to:
- 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 within the Data Science Community;
- Use advanced mathematical models, machine learning algorithms, operations research techniques, and strong business acumen to deliver insight, recommendations, and solutions (Genomics team may use following: 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.
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:
- Bachelor’s degree with at least five years of experience or Masters degree with at least two years of experience or PhD;
- Educational preparation or applied experience in at least one of the following areas: Machine Learning, Electrical/Industrial Engineering, Operation Research, Statistical Genetics, Statistics, Biostatistics, Bioinformatics, Genomics, Computational Biology, Applied Mathematics, Computer Science or other related quantitative discipline;
- Demonstrates intermediate proficiency in computational skillsand level of experience building data models using R, Python or other statistical and/or mathematical programming packages;
- Strong proficiency in predictive modeling to include comprehension of theory, modeling/identification strategies and limitations and pitfalls;
- Intermediate proficiency in machine learning algorithms and concepts;
- Experience in successful delivery of valuable analysis through application of domain knowledge; evidence of ability to strong business acumen;
- Strong communication competencies to include presentations and delivery of complex quantitative analyses in a clear, concise and actionable manner to extended team and small groups of key stakeholders.
Entirely remote jobs that could be performed in Colorado: employees can expect to be paid a salary of approximately $120,000 (or between $100,000 to $135,000). 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.Entirely remote jobs that could be performed in Colorado: employees can expect to be paid a salary of approximately $115,000 (or between $101,000 to $135,000). 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.