Data Scientist

Subway•Miami, FL

4d•Onsite

About The Position

Ready for a fresh, new career? Look no further because one of the world’s most iconic brands can help you get there. 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.

Requirements

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)
SQL along with Python, R required

Nice To Haves

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)
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
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
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

Responsibilities

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.