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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Scientist - **Company:** Nestlé Purina - **Location:** St. Louis, MO, United States - **Salary:** $88,000.0 - $123,000.0 - **Contract:** Permanent contract - **Skills:** Amazon Web Services, Data Analysis, Microsoft Azure, Continuous Delivery, Continuous Integration, DevOps, Distributed Computing Environment, Python (Programming Language), Machine Learning, NumPy, Standard Sql, Azure Machine Learning, SQL Databases, Data Processing, Cloud Platform System, Feature Engineering, Large Language Models, Snowflake, Prompt Engineering, Model Validation, Pandas, Pyspark, Scikit Learn, Kubernetes, Information Technology, Machine Learning Operations, Software Version Control, Databricks - **Published:** July 17, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=788999513395c430 ## About the Role * Bachelor's degree from an accredited institution in Data Science, Computer Science, Statistics, Engineering, Mathematics, or a related field * 3+ years of professional experience in data science, analytics, or machine learning, including developing optimization or predictive models * 3+ years of experience in Python (e.g., scikit-learn, pandas, PySpark, and NumPy) and SQL for data manipulation and analysis * 1+ years of experience working with cloud computing platforms (e.g., Azure, AWS, or GCP) and DevOps/CI-CD practices, * Master's degree in Data Science, Computer Science, Statistics, Mathematics, or a related field is preferred * Experience with MLOps tools (e.g., MLflow, Azure ML, SageMaker, or Kubeflow) and model deployment in a production environment is preferred * Experience working with Databricks, Snowflake, or distributed data processing environments is preferred * Experience building GenAI-enabled applications such as RAG, copilots, or intelligent assistants is preferred * Familiarity with LLM orchestration frameworks (e.g., LangChain or Semantic Kernel), prompt engineering, and vector databases is preferred * Familiarity with responsible AI practices including bias detection, explainability, and governance is preferred Don't meet all the qualifications listed under "Other"? These are preferred, but not required. When you apply for a role with Nestlé, we ensure that individual confidentiality is held to the highest regard. We are intentional about creating an inclusive workplace for everyone. We consider our associates our most valuable assets. Please apply for full consideration. ## Description Digital Transformation is at the center of all that we do. With data-driven innovators passionate about making a difference in the lives of pets, we create cutting-edge digital business models that solve complex problems. You'll be at the forefront of digital advancements as they happen in real time, as well as ensure we remain a leader and innovator in the pet care category. Have a hand in making a lasting impact within our long-standing history. As a Data Scientist at Nestlé Purina, you'll build and deploy the machine learning and optimization models that drive real business value across functions such as Manufacturing, Marketing, Supply Chain, Finance, and Consumer Insights. At the core of this role is traditional machine learning and optimization, building the models and optimization engines that power some of our highest-value business decisions. Working closely with cross-functional teams, you'll translate business problems into scalable analytical solutions, automate insights, and support enterprise decision-making. * Develop and deploy machine learning, statistical, and optimization models that solve business problems and improve operational performance * Support the development and maintenance of optimization engines that drive high-value business decisions * Collaborate with product owners, data engineers, and business stakeholders to translate business needs into scalable analytical solutions * Perform data wrangling, feature engineering, exploratory data analysis, and model evaluation using Python and SQL * Design and maintain reusable analytics workflows and automated pipelines for production-grade deployment * Support GenAI-enabled applications including retrieval augmented generation (RAG), copilots, and intelligent assistants * Contribute to AIOps/MLOps practices including model versioning, monitoring, continuous integration and continuous deployment pipelines, and responsible AI processes ## Related Videos - [Vectorize all the things! 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