Data Scientist

• Write production-level code for robust analytics products, ensuring scalability and maintainability.
• Collaborate with data and software engineers to support data science solutions through the entire product lifecycle, including data wrangling, exploratory analysis, hypothesis testing, modeling, rapid prototyping, business validation and testing, and deployment.
• Leverage a diverse set of large and unstructured data (POS data, loyalty program data, customer feedback, etc.) to derive meaningful insights and information sets that inform business decisions.
• Apply a variety of advanced analytical techniques including predictive modeling, machine learning, time series analysis, simulation, and optimization to address specific business challenges.

• Bachelor's degree in Data Science, Computer Science, Statistics, Mathematics, or a related quantitative field (or equivalent experience)
• 3+ years of experience in data science, analytics, or a related role
• Strong programming experience with Python, R, or similar languages for data analysis and model development
• Experience writing production-level code with a focus on scalability, performance, and maintainability
• Solid understanding of software development best practices (version control, testing, code reviews)

Technical Skills

• Hands-on experience with machine learning techniques such as regression, classification, clustering, and ensemble methods

• Proficiency in advanced analytics methods including:

• Predictive modeling

• Time series analysis

• Optimization and simulation techniques

Experience working with large, complex, and unstructured datasets (e.g., transactional, customer, or behavioral data)

Strong data wrangling and exploratory data analysis (EDA) skills

Experience with data visualization tools (e.g., Tableau, Power BI, matplotlib, seaborn)

SQL along with Python, R required

Data & Engineering Collaboration

• Experience working in cross-functional teams with data engineers, software engineers, and product teams

• Familiarity with data pipelines, ETL processes, and cloud-based data platforms (e.g., AWS, Azure, or GCP)

• Understanding of the full data science lifecycle, including:

• Data preparation

• Model development and validation

• Deployment and monitoring

Analytical & Business Skills

• Strong problem-solving and critical thinking skills with the ability to translate business questions into analytical solutions
• Experience applying data-driven insights to influence business decisions
• Ability to perform hypothesis testing and interpret statistical results

Soft Skills

• Excellent communication skills with the ability to explain complex technical concepts to non-technical stakeholders
• Strong collaboration and teamwork abilities
• Ability to manage multiple projects and work in a fast-paced environment

• Competitive Bonus
• Mobility Allowance
• Tuition Reimbursement
• Company Holidays
• Volunteering time
• And More.....

Compensation: The base pay range for this role is $102,700-$128,400 annually

Pay within this range will be determined in good faith based on job-related factors, which may include skills, experience, education/training, location, and internal equity.

We are Subway Headquarters! A dedicated team of professionals supporting thousands of franchisees around the globe. Location: Miami, FL Ready for a fresh, new career? Look no further because one of the world's most iconic brands can help you get there. Why Join Us? At Subway, "better" is baked into our DNA. We are a brand that believes in continued improvement ... in our lives, our businesses, and our planet. From the handshake that started our very first sandwich shop to earning our position as one of the world's leading restaurant brands, we've always embraced change and the path ahead. And today, we're making better living way easier. Our purpose is more than the food we serve in our restaurants. It's centered on fueling healthy businesses and healthier lives. It is one of the most exciting times to join the Subway team and contribute to our transformational journey.