Sr. Data Scientist

Region: 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 about 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. 

About the Role:

Subway is building out its Data Science team with the goal of better leveraging advanced analytic solutions to drive profitable growth, enhance customer experience, and optimize operations. We believe analytics will be a game-changer in the QSR industry, and we are seeking a Sr. Data Scientist to help build and scale our data science capabilities.

This role will be heavily project-based, working with leaders across the organization. The ideal candidate will bring demonstrated experience in structured problem-solving, model building and tuning, building production-level analytics products, data collection & cleansing, analytics execution, and communication of meaningful insights to diverse audiences of varying seniority and familiarity with analytic concepts. This position will have the opportunity to design and build leading analytics products that will pave the way for further data science at Subway.

Responsibilities include but are not limited to:

• Partner with leadership teams across various departments (Marketing, Operations, Supply Chain, etc.) to translate complex business problems into data science and advanced analytics solutions.
• Understand common trends and challenges in the QSR industry to design repeatable and scalable solutions that can be applied across Subway's diverse business areas.
  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.
• Clearly and concisely synthesize and communicate findings to make thoughtful recommendations by combining business savvy with analytic rigor to technical and non-technical audiences.
• Maintain expertise and awareness of emerging data science techniques, technologies, and potential business applications for AI/ML within the QSR industry.

 
Qualifications:

• Master’s degree in an analytical field such as Data Science, Computer Science, Applied Mathematics, or Operations Research. 3 additional years of related experience may be substituted in lieu of a degree.    
• 6-10 years of relevant data science experience developing and deploying production models and writing production code for analytics products.    
• Experience working with a variety of statistical and modeling techniques including hypothesis testing, supervised learning (classification and regression), forecasting, unsupervised clustering, and optimization.    
• Experience with Python, SQL, and related languages.    
• Experience gathering, interpreting, and translating business requirements into analytical solutions.    
• Demonstrated ability to communicate complex analytical concepts and results at multiple levels to technical and non-technical audiences.    
• Experience with code version control platforms like GitHub, GitLab, or Azure DevOps.    
• Deep expertise with a variety of data science and analytics applications applicable to quick service restaurants including marketing, loyalty and customization, offer targeting, site selection, etc.    
• Experience leveraging first party data (combined with 3rd party) to create an addressable audience-based media segmentation.    
• Experience with relevant modeling techniques including marketing mix models, A/B testing, and other experimental design methods    
• Strong background in statistical model building and tuning, with proven experience in hypothesis testing, regression analysis, time series forecasting, and other advanced statistical techniques.    
• Experience with AWS SageMaker and related AWS services for building, deploying, and managing machine learning models in production.
• Experience with large scale data wrangling using Spark or similar tools.    
• Experience working in a fast-paced deadline driven environment, ideally within the restaurant or retail industry.    
• Demonstrated high level of integrity, accountability, character, and professionalism. 
• Excellent mathematical, analytical, and problem-solving skills.    
• Excellent verbal, written and interpersonal communication skills. Ability to communicate at all levels of organization.    
• Strong commitment to delivering quality, accurate work with a passion for solving complex business problems through factual analytics
• Ability to manage competing priorities in a fast-paced environment with strict deadlines.    
• Team player who enjoys collaborating with high-intellect colleagues and stakeholders across various functions and backgrounds.    
• Strong sense of urgency, adaptability, flexibility, and resourcefulness.    
  Entrepreneurial, agile mindset; someone who wants to take part in building a world-class analytics organization.    
• Quick learner, high curiosity; strong problem solving and conceptual skills.

What do we Offer?
 
•    Insurance Plans (Medical/Life)
•    401K
•    Competitive Bonus
•    Mobility Allowance
•    Tuition Reimbursement
•    Company Holidays
•    Volunteering time
•    And Many More…..
 
 
Actual pay is determined based on a number of job-related factors including skills, education, training, credentials, qualifications, scope and complexity of role responsibilities, geographic location, performance, and working conditions.