Zostań członkiem zespołu NIKE, Inc.

NIKE, Inc. to nie tylko firma, która ubiera najlepszych sportowców na świecie. To miejsce, w którym możesz odkryć swój potencjał, przekroczyć granice oraz sprawić, że niemożliwe staje się możliwe. Firma poszukuje ludzi, którzy chcą się rozwijać i potrafią myśleć, marzyć oraz tworzyć. Jej kultura rozwija się dzięki różnorodności i wspieraniu kreatywności. Potrzebni są w niej ludzie ambitni, urodzeni liderzy i prawdziwi wizjonerzy. W NIKE, Inc. każda osoba wnosi do gry swoje umiejętności oraz pasje. Dzięki temu ciągle się rozwijamy.

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

The annual base salary for this position ranges from $107,700.00 in our lowest geographic market to $212,600.00 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.

WHO WE ARE LOOKING FOR

We are looking to hire four (4) Data Scientist III’s to join our Consumer Product & Innovation team as part of this job posting.

We’re looking for a Data Scientist III to join our Reporting + Intelligence team in the Consumer Product & Innovation organization. You will work with diverse cross-functional team members leveraging data-driven insights and AI to inform and optimize all stages of Nike's merchandising and apparel & footwear product creation lifecycle. 

WHAT YOU WILL WORK ON

You will partner with cross-functional teams to develop data-driven insights, predictive models, and optimization solutions for Nike's apparel and footwear product merchandising, design and development functions.  Leveraging your deep expertise in statistical analysis, machine learning, and applied data science you will help solve complex problems across the apparel and footwear product lifecycle.  You will be responsible for developing scalable models, conducting exploratory data analysis, and generating actionable insights that drive data-driven decisions for our merchants and creators.

You will be responsible for:

  • Developing and implementing statistical models and machine learning algorithms to analyze relevant structured and unstructured datasets and variables (Merchandising Product Lines and Assortments, Apparel & Footwear Design and Development, Sales, Consumer Behavior, Market Trends. etc.)

  • Developing ML models and planning end-to-end ML model experiment design

  • Understanding and translating business needs and objectives into the appropriate modeling technique

  • Applying hypothesis testing, regression, A/B testing and time-series forecasting to product creation decisions and timelines

  • Building and maintaining predictive/prescriptive models for scale working closely with ML Engineers to turn successful prototypes in to new AI products

  • Working closely with product and engineering teams to build, support, and scale these data-driven insights into product merchandising plans & assortments and product design recommendations

  • Evaluating existing ML and statistical products to ensure continued high-quality results and outputs

  • Performing data and error analysis to improve model performance

  • Creating clear and compelling visualizations to communicate findings and recommendations

  • Identifying and making recommendations on analytical tools, research tools, methods

WHO YOU WILL WORK WITH

You will spend much of your time with peer data scientists, machine learning engineers, and merchandising, apparel and footwear creation Product Managers in CP&I delivery teams. 

WHAT YOU BRING

  • PhD in Data Science, Applied Statistics or related field. Will accept any suitable combination of education, experience and training.

  • Strong statistical and mathematic foundation.  Solid understanding and practical application of statistical concepts, probability and hypothesis testing

  • Extensive experience with cloud tools for data science, machine learning and modeling, and visualization e.g., PySpark, Databricks, MLFlow, Jupyter Notebooks, RStudio, pandas, SageMaker, Tableau, PowerBI

  • Expertise in languages like Python, SQL, and R and for data manipulation, analysis and model building

  • Machine learning algorithms and techniques - you have a tool belt of techniques you can draw from and pick the right one for the business problem at hand

  • Demonstrated ability to proactively engage with business stakeholders, listen deeply to business challenges, and translate them into well-defined data science problems using the most effective analytical techniques.

  • Systems thinker—skilled at seeking to understand the broader context, inputs, dependencies, and external effects that shape business problems, ensuring solutions are robust and impactful.

  • 3+ years of experience building models including deep learning, neural network algorithm development

  • Prediction, Forecasting, A/B testing, complex modeling and data analyses

  • GenAI and building LLM prototypes

  • Developing and running simulation and optimization tools to support decision making

  • Ability to visualize data in the most effective way possible

  • Ability to communicate complex data in a simple, actionable way to non-technical audiences and leadership teams

  • Ability to work independently and with a diverse team

We offer a number of accommodations to complete our interview process including screen readers, sign language interpreters, accessible and single location for in-person interviews, closed captioning, and other reasonable modifications as needed. If you discover, as you navigate our application process, that you need assistance or an accommodation due to a disability, please complete the Candidate Accommodation Request Form.

Czego możesz oczekiwać

NASZ PLAN ZATRUDNIENIA

1. Aplikuj

Nasze zespoły składają się z osób o różnych umiejętnościach, wiedzy, pomysłach i doświadczeniach, a każda z nich może dać od siebie coś innego. Chcemy, żebyś znalazł(a) tu coś dla siebie – zapoznaj się z opisami stanowisk, działami i zespołami, aby odkryć, jakie stanowisko będzie dla Ciebie odpowiednie.

2. Poznaj osobę rekrutującą lub przystąp do oceny

W przypadku stanowisk korporacyjnych rekruter(ka) skontaktuje się z Tobą w celu rozpoczęcia procesu rekrutacyjnego i przez cały okres jego trwania będzie pozostawać z Tobą w kontakcie. Rekrutacja na stanowisko związane ze sprzedażą wymaga przeprowadzenia procesu interaktywnej oceny, który obejmuje czat i quizy, a jego ukończenie zajmuje około 10–20 minut. Niezależnie od stanowiska, chcemy jak najlepiej poznać naszych kandydatów i nasze kandydatki, więc zachęcamy do opowiedzenia nam o tym, jak rozumiesz pojęcie obsługi klienckiej na światowym poziomie oraz co sprawia, że jesteś osobą wyjątkową.

3. Rozmowa kwalifikacyjna

Warto podejść do tego etapu z pewnością siebie. W tym celu zapoznaj się z naszymi oczekiwaniami i przygotuj się na pytania, które pomogą nam pogłębić wiedzę o Tobie i Twoim doświadczeniu.

Dwie osoby uśmiechające się i obejmujące w plenerze