Role Description Design, develop, and implement advanced data science models and machine learning solutions for key business use cases across online experience, marketing, merchandising, and store operations. - Apply advanced data science techniques to large datasets and collaborate with cross-functional groups to derive actionable insights and develop scalable AI solutions. - Execute best-in-class advanced analytics with scalable and reusable codebase and models that solve business problems. - Generate and test hypotheses that align with priority use case. - Comply with analytics standards, including guidelines for tailoring analytics methodologies to specific use case needs (e.g., ML, AI, descriptive analytics). - Define internal or external, batch or real-time streaming data needs, evaluate data quality, and extract/manipulate data in a "Big Data" environment. - Create compelling interactive visualizations and presentations to enhance decision-making capabilities throughout the company. - Work with Data Engineering team as required to implement data pipelines and tools to ensure efficient and seamless execution of analytics. - Be agile in identifying data issues and taking action to remediate. - Provide support for business users to leverage insights and provide high value impact. - Maintain an up-to-date view on methods being used in the data science community. - May telecommute. Qualifications - Master’s degree in Statistics, Computer Science, Business Analytics or related field. - 2 years of experience as Data Scientist or related occupation. Requirements - Building data models and pipelines to process different types of large datasets. - Fluency with complex algorithms and analytics methodologies across multiple platforms and languages, including Google Cloud Platform. - SQL and Python. - Core analytical and statistical methods, including regression, segmentation/clustering, predictive modeling, time-series analysis, and machine learning techniques. - Visualization tools such as Tableau and Power BI. - Collaborating with business functions to deliver solutions that support decision making. - Analyzing data to identify deliverables, gaps, and inconsistencies. - Data management and data modeling. - Version control with Git using tools, including PyCharm and VS Code.

• Develop and maintain supervised machine learning models to support ad targeting, measurement, and campaign optimization. • Perform data analysis, data validation, and feature engineering on large and complex datasets. • Collaborate with product, engineering, and analytics teams to translate business needs into data science solutions. • Evaluate model performance using appropriate metrics and iterate on model improvements. • Support optimization and experimentation efforts related to advertising performance. • Assist with deploying models to production in collaboration with engineering teams. • Monitor model performance and help troubleshoot issues in production. • Communicate results, insights, and limitations to both technical and non-technical stakeholders. • Stay up to date with industry best practices in data science and machine learning.

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.