Data Scientist - Machine Learning

Wingstop • Dallas, TX

4h • Onsite

About The Position

This role contributes to Wingstop’s success by bridging data science and production engineering — deploying, optimizing, and scaling machine learning systems that power data-driven decisions across the enterprise. The Data Science Analyst is responsible for taking models from development to production, ensuring they are robust, efficient, and maintainable. While data science work remains part of the role, the primary focus is on deployment pipelines, infrastructure management, and code optimization that enable the broader analytics organization to deliver impact at scale.

Requirements

• Bachelor’s or Master’s degree in a quantitative field (e.g., Statistics, Mathematics, Computer Science, Engineering, Economics, or related discipline).
• At least 3 years of industry experience in ML engineering, software engineering, or a related role, with proven production ML deployment experience.
• Strong proficiency in Python; experience with software engineering practices including version control, testing, and code reviews.
• Experience with cloud data platforms such as Snowflake (including Snowpark) and cloud infrastructure (AWS, Azure, or GCP).
• Hands-on experience with Python, Java, or Scala; demonstrated ability to write production-grade, reusable code to automate ML pipelines and data workflows.
• Experience with containerization and orchestration tools (e.g., Docker, Kubernetes, Airflow, or similar) for managing ML workflows.
• Experience with data and analytics tools (e.g., Snowflake, Profisee, SAP BW, Power BI, Tableau)

Nice To Haves

• Cloud or ML engineering certification (e.g., SnowPro Advanced, AWS Certified ML Specialty, Google Professional ML Engineer) preferred.
• Experience with ML deployment on Snowflake
• Experience building and tuning time series forecasting or demand prediction models
• Experience with CI/CD pipelines for ML systems (e.g., GitHub Actions, Jenkins, MLflow, or similar MLOps tools)
• Experience in restaurant, retail, or hospitality
• Experience with SDLC methodologies, including Agile frameworks (Scrum, SAFe, Kanban)
• Understanding of Master Data Management principles, architectures, and patterns

Responsibilities

• Work closely with stakeholders to understand business objectives and requirements.
• Partner with data scientists, analytics engineers, and platform teams to move models from experimentation into production-ready systems.
• Design, build, and maintain end-to-end ML pipelines for training, validation, deployment, and retraining.
• Manage and optimize cloud infrastructure (e.g., Snowflake, AWS, Azure) to support scalable ML workloads and reduce operational cost.
• Write clean, efficient, reusable code for ML pipelines and data processes; enforce engineering best practices through code reviews and documentation.
• Profile and optimize inference latency, memory usage, and throughput for models serving real-time or batch workloads.
• Automate testing, CI/CD workflows, and deployment processes to ensure reliable, repeatable model releases.
• Own the deployment of ML models into production environments, including containerization, versioning, and API development.
• Integrate ML models into existing business systems and data workflows, working closely with software and data engineering teams.
• Continuously tune and improve deployed models, tracking performance drift and triggering retraining as needed to maintain accuracy and reliability.
• Monitor and alert relevant teams to key metrics and KPI’s.
• Support data science efforts occasionally including exploratory analysis, feature engineering, and model prototyping where needed.
• Develop dashboards and monitoring tools in Power BI or Streamlit Apps or similar platforms to surface model health, data pipeline status, and key operational KPIs.

Benefits

• Unlimited paid time off for exempt employees
• One paid volunteer day of your choice
• Competitive bonus structure for eligible roles
• Team member stock purchase plan
• Health savings or flexible spending account options
• 401k – (dollar for dollar on the first 3% and then 50 cents on the dollar for the next 2% for team member contributions up to 5% of eligible compensation)
• Comprehensive medical, dental, and vision benefits
• Basic life and AD&D insurance provided
• Pet insurance
• Education Assistance
• Wellness reimbursement program
• Paid maternity and paternity leave
• Lunch provided every Tuesday and Thursday in office
• Discount on Wingstop gift cards
• Onsite game room and patio

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level