Sr. Data Scientist Position Available In Miami-Dade, Florida

Job Description:

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

Why JoinUs?

At Subway, “better” is baked into our DNA. We are a brand thatbelieves in continued improvement

• in our lives, our businesses,and our planet.

From the handshake that started our very firstsandwich shop to earning our position as one of the world’s leadingrestaurant 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 ourrestaurants. It’s centered on fueling healthy businesses andhealthier lives.

It is one of the most exciting times to join theSubway team and contribute to our transformational journey.

Aboutthe Role:

Subway is building out its Data Science team with the goalof better leveraging advanced analytic solutions to driveprofitable growth, enhance customer experience, and optimizeoperations. We believe analytics will be a game-changer in the QSRindustry, and we are seeking a Sr. Data Scientist to help build andscale our data science capabilities.

This role will be heavilyproject-based, working with leaders across the organization. Theideal candidate will bring demonstrated experience in structuredproblem-solving, model building and tuning, buildingproduction-level analytics products, data collection & cleansing,analytics execution, and communication of meaningful insights todiverse audiences of varying seniority and familiarity withanalytic concepts. This position will have the opportunity todesign and build leading analytics products that will pave the wayfor 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 complexbusiness problems into data science and advanced analyticssolutions. Understand common trends and challenges in the QSR industry todesign repeatable and scalable solutions that can be applied acrossSubway’s diverse business areas. Write production-level code for robust analytics products, ensuringscalability and maintainability. Collaborate with data and software engineers to support datascience solutions through the entire product lifecycle, includingdata wrangling, exploratory analysis, hypothesis testing, modeling,rapid prototyping, business validation and testing, anddeployment. Leverage a diverse set of large and unstructured data (POSdata, loyalty program data, customer feedback, etc.) to derivemeaningful insights and information sets that inform businessdecisions. Apply a variety of advanced analytical techniques includingpredictive modeling, machine learning, time series analysis,simulation, and optimization to address specific businesschallenges. Clearly and concisely synthesize and communicate findings tomake thoughtful recommendations by combining business savvy withanalytic rigor to technical and non-technical audiences. Maintain expertise and awareness of emerging data sciencetechniques, technologies, and potential business applications forAI/ML within the QSR industry.

Qualifications:

Master’s degree in an analytical field such as Data Science,Computer Science, Applied Mathematics, or Operations Research. 3additional years of related experience may be substituted in lieuof a degree. 6-10 years of relevant data science experience developing anddeploying production models and writing production code foranalytics products. Experience working with a variety of statistical and modelingtechniques including hypothesis testing, supervised learning(classification and regression), forecasting, unsupervisedclustering, and optimization. Experience with Python, SQL, and related languages. Experience gathering, interpreting, and translating businessrequirements into analytical solutions. Demonstrated ability to communicate complex analytical conceptsand results at multiple levels to technical and non-technicalaudiences. Experience with code version control platforms like GitHub,GitLab, or Azure DevOps. Deep expertise with a variety of data science and analyticsapplications applicable to quick service restaurants includingmarketing, loyalty and customization, offer targeting, siteselection, etc. Experience leveraging first party data (combined with 3rdparty) to create an addressable audience-based mediasegmentation. Experience with relevant modeling techniques includingmarketing mix models, A/B testing, and other experimental designmethods Strong background in statistical model building and tuning,with proven experience in hypothesis testing, regression analysis,time series forecasting, and other advanced statisticaltechniques. Experience with AWS SageMaker and related AWS services forbuilding, deploying, and managing machine learning models inproduction. Experience with large scale data wrangling using Spark orsimilar 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-solvingskills. Excellent verbal, written and interpersonal communicationskills. Ability to communicate at all levels of organization. Strong commitment to delivering quality, accurate work with apassion for solving complex business problems through factualanalytics Ability to manage competing priorities in a fast-pacedenvironment with strict deadlines. Team player who enjoys collaborating with high-intellectcolleagues and stakeholders across various functions andbackgrounds. Strong sense of urgency, adaptability, flexibility, andresourcefulness. Entrepreneurial, agile mindset; someone who wants to take part inbuilding a world-class analytics organization. Quick learner, high curiosity; strong problem solving andconceptual 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 factorsincluding skills, education, training, credentials, qualifications,scope and complexity of role responsibilities, geographic location,performance, and working conditions. #J-18808-Ljbffr