Data Scientist - Remote

Key Skills

Analytical and Problem solving, AWS, Dash framework, Data Analysis, Data science techniques, Data Visualization, Docker, Github, Google Cloud Platform (GCP), Java Programming, Machine learning techniques, Python Programming, R Programming, R-Shiny, SQL

Job Description

The primary responsibilities of this role, Data Scientist, are to:

• Deliver best-in-class analytics solutions for the customer-centric commercial operations of Bayer Crop Science Topics such as customer analytics, segmentation analysis, pricing, demand forecast, and risk models;
• Develop practical, interpretable, and automated solutions for these business problems through expertise in statistical analysis, predictive modeling, simulation, and optimization methodology by working in a highly interactive, team-oriented environment;
• Write model documentation to detail problem formulation, modeling approach, validation, data requirements, and implementation steps;
• Support stakeholder requests for model development, implementation, and feature improvements;
• Be able to communicate results to a broad range of audiences in a clear, interpretable manner;
• Work closely with data science teams and business partners to break down complex business problems, and gather requirements to build feasible solutions that are impactful, accurate, and validated;
• Collaborate with system integration and data warehouse engineers on data extraction and data cleaning;
• Be creative, resourceful, detail-oriented, and able to take initiative and exercise critical thinking when it comes to problem-solving;
• Be a proactive member of a global data science team to adopt and advocate for coding best practices and documentation.

 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:

• Bachelor’s degree with at least six years or more of experience;
• Master’s degree with four years or more of experience or a Ph.D. with two years or more of experience including post-docs in at least one of the areas below:

• Economics;
• Physics;
• Applied mathematics;
• Computer sciencanother related quantitative discipline;

• Experience conducting statistical inferences, time-series analysis, statistical simulated ion, and analysis using disparate sources of data;
• Advanced programming skills in either R or Python for machine learning tasks, proficient in version-control tools (such as GitHub);
• Cloud engineering skills including AWS, AWS Fargate, Docker, API backend setup;
• Experience working with SQL, GCP, CRM (Salesforce) tools, and interactive visualization tools such as R-shiny and Dash;
• Excellent work ethic and a strong desire to learn new skills for technical and professional growth.

 Preferred qualifications:

• Experience in related fields where data science techniques are used, including agriculture, economics, econometrics, biology, math, physics, and engineering;
• Experience in collaborating with business partners and team members to build end-to-end analytical solutions.