YOUR TASKS AND RESPONSIBILITIES

The primary responsibilities of this role, Data Science Lead, Product Advancement, are to: 

• Direct supervision of and career development for growing team of 7-10, and developing technical leadership layer within the team;
• Create and maintain a multiyear pipeline for platform-specific discovery, development of high performing, highly scalable models, validation, and deployment of analytic models and related enabling technologies in the space of breeding product development;
• Engage with domain experts to define requirements for the above said models, define and develop alternative approaches, training data creation and curation, model creation, documentation and validation, partner with the deployment teams to deploy these models globally across different crops;
• Communicate the impact of the analytics on the research pipeline with peers and leadership;
• Stay on the cutting edge of technology in the space of new ML methodologies, cloud and edge computing, data and software engineering;
• Collaborate with Industry and Academia on various research topics;
• Participate in evaluation of select third party technologies, and provide recommendations for future technical strategies;
• Ensure team adherence to best practices as defined by Data Science Center of Excellence, including but not limited to agile/scrum, phased project advancements, code documentation and review, information security, intellectual property documentation;
• Partner with teams across the enterprise to deploy models to production, including production ready code, data I/O, stakeholder engagement and training, long term plans for support and monitoring sustainable performance;
• Manage annual expense budget of $1-2M;
• Provide thought leadership within APD analytics leadership including but not limited to best hiring practices, data science career architecture, external data science collaborations, data science branding and visibility, data science best practices;
• Participate and Lead Precision Breeding Technical initiatives.
   

 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. degree (more than eight years of related experience) in Engineering, Physics, statistics, mathematics, computer science, bioinformatics, Plant Breeding, Quantitative genetics;
• Demonstrated people leadership skills;
• A breadth of statistical and analytical techniques including but not limited to Deep Learning, Probabilistic inference, Linear models, Bayesian Inference, Simulations, Optimization methods;
• More than two years of experience of applying ML technologies to drive business outcomes;
• Experience with Machine Learning frameworks such as TensorFlow & scikit- learn, IaaS and PaaS such as AWS, Google Cloud & experience with big data stack;
• Influencing multidisciplinary teams;
• Excellent verbal and written communication skills Experience working within Ag industry is a plus.