Lead Data Scientist (Remote Work Option)

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

The annual base salary for this position ranges from $119,400.00 in our lowest geographic market to $267,500.00 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.
 

Become a Part of the NIKE, Inc. Team

NIKE, Inc. is a place to explore potential, push boundaries and push out the edges of what can be. The company looks for people who can grow, think, dream, and build. Its culture thrives by embracing diversity and exciting inventiveness. At NIKE, Inc. it’s about each person bringing skills and passion to an exciting and constantly evolving game!

Who we are looking for

Working at Nike in this time of growth and dynamic strategic intent is a unique opportunity; we are looking for a professional who is passionate about the Nike brand, energetic and proactive, and thrives on working at the intersection of data and business.

We’re looking for a Lead Data Scientist to join Nike’s Global Consumer Data Science organization, supporting the measurement of our Consumer Marketing channels to optimize Nike’s marketing strategy.

This is a new position in the Marketing Data Science team, which will focus on evolving Nike’s Marketing Mix Modeling (MMM) capability, playing a meaningful role in shaping how marketing effectiveness is measured.

We seek an individual with hands-on experience in MMM. This person will be comfortable getting their hands dirty with exploratory data analysis, coding, and modeling. They will also collaborate with team-members and partners, assuring that we are crafting the best solutions for evolving business needs.

A successful candidate has a comprehensive grasp of the MMM development process, and experience leveraging standard data science tools (PySpark, Pandas, Scikit, XGBoost, etc.), platforms (i.e. Databricks, Sagemaker, Python) and cloud providers (AWS/MS Azure). As a lead data scientist in the team, you will be responsible for designing and developing innovative measurement and marketing mix models, while coordinating with fellow data scientists, marketers and machine learning engineers to solve key challenges facing the teams.

What you will work on

This person will join a team that is responsible for measurement and optimization of Marketing Effectiveness on behalf of the Marketing organization. You will work closely with Data Science and Marketing Science teammates to build, support, and enable Marketing/Media Mix Modeling (MMM) and related forecasting & budgeting use cases.

Build credibility for MMM approaches through demonstrating functional expertise and experience. Simultaneously innovating to drive more granular and frequent measurement, and broader adoption across the organization.

Establish and support large-scale measurement and optimization of MMM for different geographies in a production/testing environment.

Improve and consult on MMM to connect the impact of marketing drivers and business short-term and long-term outcomes.

Partner with peers in both Data Science and Marketing Science, developing scalable data, improving current MMM models, and modeling processes. Use common tools and instruments to help establish operational excellence for MMM.

Drive the application and implementation of innovative best-in-class methods and tools to derive useful insights for a wide variety of business goals in support of marketing efforts.

Stay up to date on industry trends, tools, and platform capabilities relevant to the team’s disciplines.

Who you will work with

Reporting to the Director of Marketing Data Science, you will work with internal teams across Global Insights, Data Science & Analytics as well as external media agencies and platform partners, to build and deploy consistent and scalable measurement solutions.

What you bring

• Bachelor’s degree in Mathematics, Statistics, Machine Learning, Data Science, or related quantitative field preferred
• 4-7 years of hands-on experience, industry experience in the development of marketing mix models, real-time forecasting, and optimization media tools
• Advanced programming skills using Python and SQL
• Hands-on experience with standards data science & analytics tools like PySpark, Pandas, Scikit, XGBoost, etc.
• Experience with cloud based platforms and providers (i.e., AWS, Databricks, Sagemaker, Microsoft Azure).
• Hands-on experience with marketing mix platforms, such as the following: PyMC, Google’s LightweightMMM, Google’s Meridian or Facebook’s Robyn.
• Hands-on experience with advanced statistical and/or machine learning methodol