Data Scientist

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.

Data Scientist 

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 creating system analysis, developing prototype solutions using scientific programming languages, designing experiments (DOE) for validation, testing efficiency of models and measuring its impact;
• Build cross-functional relationships to collaboratively partner with the business and effectively network within the Data Science Community;  
• Development & deployment of new operations research methods to advance pipeline and product development;
• Analyze & observe existing big data operations systems to identify areas for optimization opportunities;
• 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:

Required Qualifications:

• M.S.
• Relevant work experience in a quantitative discipline (Operations Research, Mathematics, Computer Science, Computational Biology, Genomics, Industrial Engineering)
• Hands-on experience in deterministic optimization and algorithm development related to operations management involving math programming techniques such as linear, integer programming, stochastic programming, statistical and machine learning methods;
• Experience with one or more optimization toolkits/libraries like CPLEX, Gurobi, XPressMP, Open-source solvers (CBC, GLPK) etc.;
• Strong skills in programming, scientific computation, statistical packages, and database languages (R, Python, Scala, SQL, Spark, C++);  
• Ability to identify new problems and opportunities in the space of operation management and decision making, and design innovative solutions with clear deliveries and business values; • Ability to communicate your results from deeply technical to non- technical audiences in a clear, concise, and actionable manner;
• Ability to collaborate with and influence cross functional leaders from various regions. Desired Skills and Experiences  
• You have proven experience in leveraging operations research/data science to solve business problems in an industrial setting;  
• You have proven ability as a full stack operations research/data scientist who develops, optimizes, and scales models for the production environment;
• You have proven experience with statistical methods and advanced machine learning techniques (e.g., Random Forest, SVM, Computer Vision, Neural Networks) along with the optimization and OR techniques;
• You have proven experience with Cloud platforms and technologies such as AWS, Azure, and GCP as well as with TensorFlow;  
• You have domain knowledge related to industrial manufacturing, planning and scheduling, agricultural production, greenhouse nursery operations, and crop science.

Preferred

• Ph.D/M.S. with 2 years of relevant work experience in a quantitative discipline (Operations Research, Mathematics, Computer Science, Computational Biology, Genomics, Industrial Engineering);