Nike SENIOR DATA SCIENTIST (LAB 222) in Boston, Massachusetts
What you bring
Advanced quantitative degree (Statistics, Mathematics, Economics, Computer Science or related field) and at least 5 years of related industry experience or Bachelor’s degree and 7-12 years related industry experience.
Demonstrated expertise with data science methods, machine learning algorithms and production level programming principles.
Working knowledge of forecasting techniques, such as surveys, trend analysis, econometric models and machine learning algorithms.
Advanced skills in programming languages (particularly Python, Pandas and SQL) and ability to apply them to develop, build and maintain production grade analytics software.
Knowledge of mathematical optimization modeling and algorithms highly desired. Linear and Mixed Integer programming in particular.
Demonstrated ability to apply programming skills to data acquisition, preprocessing, modeling and monitoring as well as familiarity with the wide range of data science/analytics software tools.
Experience with common data science/analytics software tools (e.g. Jupyter Notebook, SQL, Spark, Git) and cloud computing platforms (e.g. Amazon Web Services).
Experience in building, training, scoring, tuning and maintaining predictive models in production at enterprise scale and familiarity with mainstream packages relevant to managing all stages of Data Science/Analytics lifecycle.
NIKE, Inc. is a growth company that looks for team members to grow with it. Nike offers a generous total rewards package, casual work environment, a diverse and inclusive culture, and an electric atmosphere for professional development. No matter the location, or the role, every Nike employee shares one galvanizing mission: To bring inspiration and innovation to every athlete* in the world.
NIKE, Inc. is committed to employing a diverse workforce. Qualified applicants will receive consideration without regard to race, color, religion, sex, national origin, age, sexual orientation, gender identity, gender expression, veteran status, or disability.
Analytics is a competitive differentiator for Nike and is fundamentally changing how the company serves athletes and consumers around the world! Our Nike Commercial Analytics team builds analytic-based solutions to manage marketplace and optimize the supply chain. Using big data, advanced analytics and state-of-the-art technology, the team strives to ensure that Nike gets the right product to the right place at the right time for the consumers
Who we are looking for
We are looking for a Senior Data Scientist to join our Advanced Analytics team within Commercial Analytics focused on unique opportunities within Nike’s growing Direct to Consumer business. This role will be part of a multi-functional agile squad responsible for using predictive analytics to forecast consumer demand, enhance decision making and drive to action against our strategic priorities. Does this sound like you?
The candidate needs to be a dependable teammate with strong hands-on analytics experience, drive, and curiosity. You know how to rise above the numbers and explain the crucial insights to users at all levels. You simplify and distill business complexity into testable hypotheses and scalable solutions. While you are well versed in a plethora of advanced modeling techniques, you are able to identify the technique optimal for the task at hand based on the business requirements, your knowledge of the data and the technique’s assumptions, interpretability and robustness. You ask good questions, are continually learning as well as finding opportunities to share knowledge with others!
What you will work on
If this is you, you will be part of an Advanced Analytics, In Season Optimization squad. We deliver scalable solutions to power data driven automated decision making on a variety of problems, such as pricing, product allocation and other related key business decisions. Specifically, you will:
Develop new sophisticated algorithms and improve existing approaches based on statistical/econometric methods, machine learning techniques and big data solutions to forecast consumer demand and determine optimal level of investment in various stages of the supply chain.
Identify and apply methods to acquire, explore, cleanse, and fuse data from different sources.
Design, write, own and maintain production grade analytics code to support forecasting and/or optimization models. Review and ensure code quality of peers.
Assess business requirements and constraints to make trade-off recommendations between speed and accuracy of alternative solution approaches.
Be a key contributor to building, scoring, deploying, monitoring, updating and promoting Nike’s central forecasting platform.
Facilitate the planning, scheduling and value measurement of the work to meet timeline targets and success criteria.
Support the adoption of analytic products through effective storytelling and collaboration with key partners.
Participate in a continuous learning environment within the advanced analytics community through persistent development of new skills and sharing of knowledge through mentorships and contributions to the open source community.
Who you will work with
You will work with the Director of Data Science while partnering daily with fellow data scientists, data analysts, engineers and product owner on your squad. You will collaborate across the broader organization with business teams in Demand and Supply Management as well as other data, analytics and technology functions at Nike.
NIKE, Inc. is committed to employing a diverse workforce. Qualified applicants will receive consideration without regard to race, color, religion, sex, national origin, age, sexual orientation, gender identity, gender expression, protected veteran status, or disability. NIKE is committed to working with and providing reasonable accommodation to individuals with disabilities. If, because of a medical condition or disability, you need a reasonable accommodation for any part of the employment process, please call +1 503-671-4156 and let us know the nature of your request, your location and your contact information.
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