Title: Senior Data Scientist Location: United States Job Description: Sr. Data Scientist for St. Louis, MO to develop predictive agronomic models to address scientific challenges in precision agriculture; manage data preparation and cleansing for multi-source agronomic data; ensure quality standards & build reliable pipelines for integration and analysis; lead implementation of research projects using statistical, machine learning & optimization techniques; review & revise code to ensure quality and reproducibility; provide mentorship and technical guidance to junior data scientists; provide coaching & training in agile framework and methodologies; coordinate sprints, retrospective meetings & stand-ups. Requires Master's in Data Science, Statistics, Applied Mathematics, or closely-related quantitative field & 4 yrs experience building predictive machine learning, statistical models, and optimization algorithms for research applications; deploying code to AWS; writing code in Python with data science packages, including Pandas, Numpy & Geopandas for data aggregation; using Matplotlib & Seaborn for data analysis & visualization; using PyMC for Bayesian statistical modeling & inference; using Sklearn & XGboost for machine learning and modeling; using TensorFlow and Keras for deep learning modeling; working with large, complex datasets across agronomic, genetics, environmental & weather domains using SQL, PySpark and Google BigQuery; designing & analyzing agronomic trial data, including experimental protocols and hypothesis testing to evaluate outcomes; using version control systems, including GitLab, to track code history & perform code review; creating & deploying CI/CD pipelines, applying MLOps best practices, including code documentation, merge/pull requests, unit testing, and code modularization; using JIRA & Agile methodologies for task prioritization and project management; communicating with technical & non-technical stakeholders at all levels of the organization, including business stakeholders, agronomists, data engineers, and data scientists. Telecommuting permitted from home office location anywhere in the U.S. Salary Range: Employees can expect to be paid a salary between $120,000.00 to $150,000.00. Additional compensation may include a bonus or commission (if relevant). Additional benefits include health care, vision, dental, retirement, PTO, sick leave, etc. The offered salary may vary within this range based on an applicant’s location, market data/ranges, an applicant’s skills and prior relevant experience, certain degrees and certifications, and other relevant factors. Mail resume to Cascinda Fischbeck, Bayer Research & Development Services LLC, 800 N. Lindbergh Blvd., E2NE, St. Louis, MO, 63167 or email resume. Include reference code below with resume. Bayer Research & Development Services LLC is an Equal Opportunity Employer/Disabled/Veterans Bayer Research & Development Services LLC is committed to providing access and reasonable accommodations in its application process for individuals with disabilities and encourages applicants with disabilities to request any needed accommodation(s) using the contact information below. If you meet the requirements of this unique opportunity, and want to impact our mission Science for a better life, we encourage you to apply now. Job postings will remain open for a minimum of ten business days and are subject to immediate closure thereafter without additional notice. Equal Opportunity Employer Statement: Notice for U.S. Visitors: All information on this site is subject to compliance with local rule and regulations as they may vary from time to time and across different geographies, including, without limitation, U.S. Executive Orders. Division:CropScience Reference Code863349 Functional Area:CDFS Location:St. Louis, MO Employment Type:Regular Position Grade: Contact Us AddressTelephone Creve Coeur, MO 63167

Experiment with and build machine learning models for government applications, tackle challenges in document processing, and operationalize AI solutions to enhance efficiency and accessibility in public services.

• Own ambiguous, high-impact problem spaces across product and business domains, from question framing, to devising and conducting the analysis, to developing and implementing solutions with cross-functional partners • Partner with cross-functional stakeholders and company leadership to shape product strategy and anticipate future challenges • Design and evaluate experiments to measure the impact of product and strategic changes • Analyze data from across the product to uncover root causes of metric movements • Develop tools, methodologies, and frameworks that help make both the data team and the company as a whole smarter about data • Multiply the impact of other data scientists through mentorship and instilling industry best practices across the team

• Design data science approaches that balance client business goals with statistical, technical, and data constraints. • Python data analysis workflows using tools such as pandas, NumPy, matplotlib/plotly, scikit-learn, SQL, git, and GitHub. • Analyze healthcare, marketing, commercial, clinical, or utilization data using methods such as natural language processing and free-text analysis, clustering, geospatial analysis, descriptive statistics, and predictive modeling. • Translate technical findings into clear data stories, visualizations, and client-ready recommendations for cross-functional stakeholders. • Support and own experimental design, data analysis workstreams, and documentation across consulting engagements.