> Markdown version of [/jobs/ext/4462236-sr-data-scientist](https://www.wearedevelopers.com/jobs/ext/4462236-sr-data-scientist). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Sr Data Scientist - **Company:** McLane Company, Inc. - **Location:** Temple, TX, United States - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Microsoft Azure, Unix, Cyber Security, Information Systems, Continuous Integration, Data Governance, Data Systems, Monitoring of Systems, Python (Programming Language), Machine Learning, Mainframes, DataOps, Cloud Platform System, Feature Engineering, Information Technology, Data Analytics, Machine Learning Operations, Docker - **Published:** October 10, 2026 - **Apply:** https://diversityjobs.com/career/18606652/Sr-Data-Scientist-Texas-Temple ## About the Role * Bachelor's degree in computer science, Information Systems, Cybersecurity, or a related field, or equivalent relevant experience. * 4 years of experience working with Security Administration across Mainframe, Unix, and Windows environments * This position requires the ability to read, write, and understand English at a level sufficient to perform job-related tasks effectively and safely. This includes understanding work instructions, safety protocols, and communications essential to the role. The requirement is directly related to the nature of the job and ensures compliance with workplace safety and operational standards. Fit the following? We want you here! * Teamwork oriented * Organized * Problem solver * Detailed ## Description McLane teammates, the driving force behind our success, are diverse professionals who work together seamlessly to keep our operations running smoothly. As a teammate, you will pair your dedication, expertise, and collaborative spirit with your fellow teammates to serve America's most beloved brands. McLane leaders think long-term, act with purpose, and inspire high performance. They lead with accountability, communicate clearly, and drive results through collaboration, innovation, and continuous growth. They empower each teammate to learn from industry leaders, develop their skills, and build lasting connections nationwide. Responsible for leading the design, development, and deployment of advanced data science and machine learning solutions that drive business value and operational efficiency. Ensures the delivery of scalable, production-grade models and analytics capabilities aligned with business objectives, data governance standards, and enterprise architecture. Operating with a high degree of independence, owns the end-to-end model lifecycle and serves as a technical leader within the data science function. Partners closely with cross-functional stakeholders to translate complex business problems into data-driven solutions and establishes best practices across ML/AI, MLOps, and DataOps disciplines. This is a hybrid position which will require the candidate to report and work from the office at least three days a week. Therefore, interested candidates should be within a 50-minute radius from Temple, TX., * Own and manage the end-to-end model lifecycle, including problem definition, feature engineering, model training, validation, deployment, and monitoring. * Build, test, and deploy production-grade models using Python, statistical methods, and modern machine learning techniques. * Implement and maintain MLOps and DataOps best practices, including CI/CD pipelines, model monitoring, and governance frameworks. * Deploy and manage models in cloud environments (GCP and Azure) using Docker and containerized workflows. * Collaborate with cross-functional teams to translate business requirements into scalable and actionable data solutions. * Establish and enforce technical standards, frameworks, and best practices for data science and model development. * Mentor and provide technical guidance to junior data scientists and team members. * Monitor model performance and ensure accuracy, reliability, and scalability of deployed solutions. * Identify opportunities to enhance data science capabilities, automation, and operational efficiency. * Clearly communicate complex analytical concepts and insights to both technical and non-technical stakeholders. * Escalate risks, issues, or model performance concerns appropriately. * Perform other duties as assigned.