Sr. Data Scientist
Company: The Subway HR Team
Location: Miami
Posted on: May 17, 2025
Job Description:
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.
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Keywords: The Subway HR Team, Bal Harbour , Sr. Data Scientist, Other , Miami, Florida
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