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.
Sr Data Scientist Nonlinear Dynamics
YOUR TASKS AND RESPONSIBILITIES
The primary responsibilities of this role, Senior Data Scientist Nonlinear Dynamics, are to:
- Provide technical contributions in a fast-paced team environment to accelerate our efforts on building an analytics-driven product pipeline;
- Perform independently 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 nonlinear (CHOAS) models, mathematical models, machine learning algorithms, operations research techniques, and strong business acumen to deliver insight, recommendations, and solutions;
- Develop sustainable, consumable, accurate, and impactful reporting on model inputs, model outputs, observed outputs, business impact, and Key Performance Indicators (KPIs);
- 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 eight years of experience OR Master’s degree with at least six years of experience OR Ph.D. with at least three years of professional and/or post doc experience in Computer Science, Mathematics, Physics, Engineering, or other quantitative disciplines;
- Experience in Optimization, Error propagation, and nonlinear dynamic analyses;
- Strong background in Machine learning with an expertise in many fields such as Tree based methods, Monte-Carlo simulations, Stochastic Modeling, Estimation and Prediction, Recommender Systems, Boosting and Bagging techniques, Bayesian analysis, Deep learning, Reinforcement learning, and Optimization;
- At least four years of experience in applying Machine/Deep learning/optimization towards solving large scale real world problems;
- At least five years of experience with at least one of R, Python, Java, Scala, C/C++;
- At least two years of experience with TensorFlow, Keras, NumPy, Scipy, NLTK (or equivalent tools);
- At least two years of experience with languages used for querying data (e.g. Hive/Pig/SQL), and/or experience with Infrastructure as a service such as AWS and Google cloud;
- Creative, proactive, bold and out-of-box thinking;
- Proven ability to communicate complex qualitative analysis in clear, precise and actionable manner;
- Strong organizational, interpersonal, and problem solving abilities;
- Ability to work in a matrix environment, leading and influencing people at varying levels of responsibility.
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.
Reference Code: 446026
Functional Area: Information Technology
Entry Level : Professional