Senior Data Scientist (Remote Work Eligible)

Open to remote work except in South Dakota, Vermont and West Virginia.

The annual base salary for this position ranges from $99,500.00 in our lowest geographic market to $222,900.00 in our highest geographic market. Actual salary will vary based on a candidate's location, qualifications, skills and experience.

Information about benefits can be found here.
 

Analytics is a competitive differentiator for Nike and is fundamentally changing how the company serves athletes and consumers around the world! Our Nike Insights Data Science and Analytics team builds analytic-based solutions to manage marketplace and optimize the supply chain. Using big data, advanced analytics and innovative 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 Sr Data Scientist to join our Merch Financial Planning Data Science team within Insights Data Science and Analytics focused overall Nike's growth over next several years. 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 sophisticated modeling techniques, you can 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 Enterprise Data Science, Merch Financial Planning squad. We deliver scalable solutions to power data driven automated decision making on a variety of planning problems 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 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 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 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.

What you bring

• Advanced quantitative degree (Statistics, Mathematics, Economics, Computer Science or related field) and at least 3 years of related industry experience or Bachelor’s degree and 5 years relevant industry experience.

• Demonstrated expertise with data science methods, machine learning algorithms and production level programming principles.

• Solid understanding 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 products.

• Knowledge and experience with demand forecast models and algorithms highly desired. Experience solving retail business problems is a plus.

• 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).

• Solid understanding of python and spark framework to leverage power of the distributed computing.

• 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.

• Exposure to the Monthly business planning process in Retail and Supply chain would be an advantage.