Data Science Manager

Overview

Have you ever enjoyed Arnold®, Brownberry® or Oroweat® bread? A Thomas’® English muffin or bagel? Or perhaps snacked on a Sara Lee®, Entenmann’s® or Marinela® cake or donut? If the answer is yes, then you know Bimbo Bakeries USA!

More than 20,000 associates in bakeries, sales centers, offices and on sales routes work to ensure our consumers have the freshest products at every meal. In addition to competitive pay and benefits, we provide a safe and inclusive work environment that appreciates diversity, promotes development and allows our associates to be their authentic selves.

Come join the largest baking company in the world and our family of 20,000 associates nationwide!

The Manager of Data Science will assist in developing and deploying advanced analytics and machine learning solutions that drive business value. This role requires expertise in statistical modeling, machine learning, and big data technologies. You will partner with cross-functional stakeholders to translate business challenges into data-driven solutions while mentoring and developing a high-performing team of data scientists.

• Advanced Data Analysis & Strategy
  • Lead the collection, cleaning, and preprocessing of complex datasets.
  • Define and implement data strategies aligned with business objectives.
• Machine Learning & AI Model Development
  • Design, develop, and deploy advanced machine learning models and AI solutions.
  • Optimize model performance through feature engineering, hyperparameter tuning, and validation.
• Big Data & Scalable Solutions
  • Work with large-scale data processing frameworks (e.g., Spark, Hadoop).
  • Implement scalable machine learning models using cloud platforms (AWS, GCP, Azure).
• Statistical Analysis & Experimentation
  • Conduct hypothesis testing, A/B testing, and causal inference analysis.
  • Apply statistical methods to derive actionable business insights.
• Data-Driven Decision Making
  • Translate complex data findings into clear insights and business recommendations.
  • Develop dashboards and reports for executive leadership using tools like Power BI, Tableau, or Looker.
• Mentorship & Leadership
  • Guide junior data scientists and analysts, providing technical mentorship and best practices.
  • Lead data science projects, ensuring timely delivery and alignment with business goals.
• Collaboration with Cross-Functional Teams
  • Work closely with engineering, product, and business teams to integrate data science solutions.
  • Communicate complex data concepts to non-technical stakeholders effectively.
• Automation & Optimization
  • Build and improve automated data pipelines and model deployment workflows (MLOps).
  • Optimize algorithms for efficiency, scalability, and real-time processing.
• Research & Innovation
  • Stay up to date with the latest advancements in machine learning, AI, and data science techniques.
  • Experiment with new tools, frameworks, and methodologies to improve analytical capabilities.
• Regulatory Compliance & Data Governance
  • Ensure data science projects adhere to privacy, security, and ethical AI standards.
  • Implement best practices in data governance and model explainability.

• Strong work ethic – ability to foster trusting relationships, demonstrate a sense of responsibility in job performance, show commitment to quality of work, exhibit discipline and dedication to complete work, and display a sense of teamwork and respect, enabling collaboration to meet goals
• Communication, listening and interpersonal skills (English, oral & written)
• Flexibility - adaptation to the changing needs and priorities in the work environment
• Work under pressure
• Ability to identify, analyze, organize and solve issues and problems in a timely and effective manner
• Team approach / cooperation - work with others, and through others, in order to meet goals, accomplish work, and resolve problems
• Customer service oriented - understand and anticipate the needs of users
• Ability to identify and pursue new ideas, solutions, methods or opportunities to increase productivity and quality
• Effectively deal with change and resistance to change
• Detailed knowledge and understanding of IT architectures and business processes
• Strong leadership…