Data Science Technical Lead

Reference Code: 69069

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.

Relocation may be offered for this role.

Direct supervision (technical, strategic) of and career development for a growing team of 3 data scientists with a focus on creating a team environment for individuals to develop and succeed;
Lead innovation using the latest advances in data science with a primary focus on machine learning, prescriptive modeling, and optimization;
Develop and deploy new solutions globally, to accelerate our pipeline and product development efforts;
Collaborate with other scientists, Software/Data Engineering leads, and Data Science leads within the group to build a technology strategy that drives the desired business outcome;
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 stakeholders from different parts of the organization to identify new opportunities that optimize total cost, recycle time, and other key metrics;
Present compelling, validated stories to all levels of the organization, including peers, senior management and internal customers to drive both strategic and operational changes in business;
Assist with technical and behavioral interviews for new hires within the organization;
Work closely with the University relations to oversee student interns;
An active participant in the Data Science Center of Excellence (DSCOE) hackathons, meetups, and speaking events.

Strong background in Machine learning with an expertise in many of the following: Tree-based methods, Monte-Carlo simulations, Stochastic Modeling, Estimation and Prediction, Recommender Systems, Boosting and Bagging techniques, Bayesian analysis, Deep Learning, Reinforcement learning, Optimization;

5+ years of experience in applying Machine learning/optimization towards solving large scale real-world problems;
5+ years’ experience with at least one of R, Python, Java, Scala, C/C++;
2+ years of experience with sci-kit-learn and pandas (or equivalent tools);
1+ 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;

Minimum of a Bachelor’s degree with 8+ yrs of experience or Master’s degree with 6+ yrs of experience or PhD with 3+ yrs of professional and/or post doc experience in Computer Science, Mathematics, Physics, Engineering or other quantitative disciplines;

Creative, proactive, bold and out-of-box thinking;
Proven ability to communicate complex qualitative analysis in a clear, precise and actionable manner;
Strong organizational, interpersonal, and problem-solving abilities;
Ability to work in a matrix environment, leading & influencing people at varying levels of responsibility.