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The Sr. Data Scientist acts as a technical lead in specific domains developing sophisticated predictive models, mining large data sets for insights, building scalable data products, and growing the overall Data Science capability at Foot Locker working with a prioritized road-map for projects.
The senior data scientist acts as an expert in a particular domain of science models and works with other data scientists to create solutions to complex business problems. You must be adept at using large data sets to find opportunities and using models to test the effectiveness of different courses of action. Experience in data analysis, visualization, and building and scaling models is imperative. You will use your proven ability to drive business results with data-based insights and be comfortable working with a wide range of stakeholders and functional teams. You will leverage your passion for discovering solutions hidden in large data sets and working with stakeholders to improve business outcomes.
Responsibilities
- Formulate, prioritize, and lead initiatives to contextualize and solve the most challenging problems in Foot Locker’s analytical portfolio
- Understand business problems and design end to end analytics use cases. Partner with business tech leads to implement reusable and robust solutions
- Apply strong expertise in machine-learning, data mining, and information retrieval to design, prototype and build the next generation analytics engine and services.
- Partner with data science leadership and engagement teams to present solutions and insights to business.
- Help maintain and track project goals and road-maps. Collaborate with software and data engineers to implement and deploy scalable solutions.
- Develop complex models and algorithms that drive innovation throughout the organization. This may include initiatives in understanding our Products, Customers, Operations, Footprint, etc.
- Mentor junior team members and provide constructive critique on specific projects.
Qualifications
- Advanced degree (MS/PhDs) in computer science, statistics, economics, physics, mathematics, operations research, or related technical discipline.
- Minimum of 4 years experience in Data Science & Machine Learning
- Experience in the retail domain is a plus
- Be a Collaborator and have a professional attitude and strong service orientation
- Strong business acumen and judgment combined with excellent verbal and written communication that can be used to drive our strategy throughout all levels of the organization
- Demonstrate organizational empathy while delivering results. Ability to build relationships quickly, collaborate and lead with courage will be a must
- Deep knowledge of machine learning and statistics
- An advanced understanding of supervised and unsupervised learning techniques including variable selection, feature engineering, model generation, model diagnostics, hyperparameter tuning, and deployment
- Excellent statistical skills that are grounded in a thorough understanding of testing and frequentist/Bayesian methodologies
- Previous experience with Neural Networks, NLP and Econometrics
- Able to work with big-data. Familiar with spark/sql, pyspark, databricks
- Good programming skills in python or R
- Excellent data visualization skills: able to determine the appropriate visualization for a variety of data types and create compelling stories with data
- Understanding of Agile methodologies and continuous delivery
- Understanding of SDLC collaboration, including experience with tools such as GIT
- Knowledge of cloud environments such as Azure is preferred