Data Analyst

Bayer•Creve Coeur, MO

7d•$71,000 - $135,000•Onsite

About The Position

As Bayer Crop Science's Digital Farming arm, we deliver sustainable digital solutions using the latest agronomic science, data science, engineering, and real-world farming experience. With groundbreaking technologies like FieldView™, our team is a part of some of the most important advancements in agriculture. The Science Technical Community is focused on creating a competitive advantage for Bayer and our customers through metrics, insights, and data services. We are an entrepreneurial team that builds and leverages state-of-the-art analytics systems. Our work informs decisions and direction for our business, while also impacting our products. Digital Farming Solutions (DFS) is seeking a Data Analyst to collaborate with Commercial, Marketing and Science teams and support the execution of global commercial strategies. The Data Analyst will work with key stakeholders and cross-functional teams to derive insights that influence decision making and improve business performance. This includes exploratory analysis of large data sets, identification of metrics/KPIs, creation of reports, storytelling and development & maintenance of data analytic processes and systems.

Requirements

Bachelor’s degree in Business, Economics, Statistics, Computer Science, Math or a related quantitative discipline and at least 2 years of relevant analytic experience.
Understanding of master data management, relational databases, columnar databases, ETL and data warehousing.
Experience with SQL and proficient with either PySpark or BigQuery for handling large-scale datasets
Ability to execute research projects and generate practical results and recommendations.
Intermediate Excel and PowerPoint skills and proficient in SQL and Python, including use of common data analysis libraries (e.g., NumPy, Pandas, Matplotlib, Seaborn).
Development experience with BI platforms like Tableau or Power BI, including building dashboards and user interfaces for cross-functional stakeholders.
Self-starter who enjoys working in both individual and team settings.
Excellent communication and collaborative skills.

Nice To Haves

Master’s degree in Data Science, Statistics or a related discipline.
Experience with AI-Assisted Development (Cursor, Copilot, MyGenAssist, Gemini, etc)
A deep understanding of statistical analysis and experiment design
Experience conducting data manipulations and analysis of geospatial and/or agronomic datasets, including formats such as WKT, Shapefile and GeoJSON
Experience applying machine learning and statistical libraries (e.g., Scikit-learn, TensorFlow, Keras) to geospatial and/or agronomic data
Experience performing geospatial data manipulation and visualization to derive insights from agricultural or biotechnology data
Familiarity with version control and CI/CD practices (e.g., GitLab, Docker, package management such as Conda or Poetry) to build, test and deploy analytics code and pipelines

Responsibilities

Be a trusted partner to DFS Leaders and other stakeholders helping them to solve problems and advance their understanding of the business.
Serve as a subject matter expert on data collected by FieldView and other sources and provide support to global teams advising them on data processes and related systems.
Work on the development of reporting solutions by interpreting business requirements and delivering innovative solutions (automated/ad-hoc reporting) to address them. Assist with storytelling by creating content that helps to visualize and interpret data trends.
Lead projects for areas of ownership and perform data exploration and validation.
Design and execute analytical experiments and perform statistical analysis as needed.
Partner with Commercial, Data Engineering and Science teams to provide better insights into product and agronomic data.
Develop the technical roadmap with the Data Engineering teams and is responsible for maintaining and documenting critical business reporting rules.
Data mining, statistical analysis, and data visualization to help understand how growers are interacting with our product.
Provide knowledge transfer, personal development to analysts through work experience and coaching/feedback.