Data Scientist

• Lead design, development, validation, deployment, and continuous improvement of forecasting, predictive, and optimization models. • Drive demand forecasting and supply chain analytics initiatives... organization. What You Will Do Translate business challenges into well-defined analytical and machine learning problem statements. Collect, clean, prepare, and analyze structured and unstructured data to uncover actionable insights. Perform exploratory data analysis (EDA) to identify patterns, trends, and opportunities. Design, build, validate, and optimize predictive, statistical, forecasting, and machine learning models. Develop robust feature engineering strategies and evaluate multiple modeling approaches to improve outcomes. Assess model performance using appropriate statistical and business metrics. Build scalable, reliable, and production-ready analytical solutions. Support solution deployment through APIs, applications, automated pipelines, dashboards, and cloud-based platforms. Monitor model performance, identify data drift, and implement continuous improvement processes. Communicate findings, recommendations, and business insights through clear visualizations and compelling narratives. Document methodologies, assumptions, data sources, and model performance to support governance, transparency, and reuse. Who You Are (Basic Qualifications) Bachelor's or Master's degree in Data Science, Statistics, Computer Science, Engineering, Mathematics, Operations Research, or a related quantitative discipline. 5+ years of experience in data science, advanced analytics, or applied machine learning. Strong programming experience in Python, including libraries such as Pandas, Num Py, scikit-learn, and statistical modeling packages. Strong SQL skills and experience working with structured and large-scale datasets. Hands-on experience with predictive modeling, forecasting, optimization, or advanced statistical analysis. Experience developing and deploying scalable, maintainable, and production-ready solutions. Experience working with large, complex, real-world datasets. Familiarity with data visualization tools such as Power BI, Tableau, or similar platforms. Strong communication, collaboration, and stakeholder management skills. Demonstrated ability to translate analytical results into business recommendations. What Will Put You Ahead Experience deploying machine learning solutions on cloud platforms such as AWS or Azure. Experience with time-series forecasting, optimization techniques, and advanced statistical modeling. Knowledge of MLOps practices including model versioning, monitoring, CI/CD pipelines, and automated retraining. Exposure to Generative AI, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and AI-assisted analytics solutions. Experience building end-to-end data products and decision-support systems. Background in engineering, applied statistics, operations research, or related quantitative disciplines. Experience influencing business decisions through data-driven insights and scalable analytical solutions. At Koch companies, we are entrepreneurs. This means we openly challenge the status quo, find new ways to create value and get rewarded for our individual contributions. Any compensation range provided for a role is an estimate determined by available market data. The actual amount may be higher or lower than the range provided considering each candidate's knowledge, skills, abilities, and geographic location. If you have questions, please speak to your recruiter about the flexibility and detail of our compensation philosophy. Who We Are At Koch, employees are empowered to do what they do best to make life better. Learn how our business philosophy helps employees unleash their potential while creating value for themselves and the company. Additionally, everyone has individual work and personal needs. We seek to enable the best work environment that helps you and the business work together to produce superior results.