Global Intelligence Analyst II

Beaverton, OR - USA

Monthly Salary: Not Disclosed

Posted on: 30+ days ago

Vacancies: 1 Vacancy

Job Summary

WHO WE ARE LOOKING FOR

Were looking for a Global Intelligence Analyst II to join the Data Analytics Intelligence team in the Nike Intelligence Center. Youll support data-driven decision-making across the enterprise by building and evaluating statistical and machine learning models designing experiments and creating clear visualizations to communicate insights. Were looking for someone who can work independently solve complex problems and clearly explain technical findings to non-technical audiences.

WHO YOULL WORK WITH

The Nike Intelligence Center powers and protects Nikes competitive advantage by providing insights into global trends risks and issues that intersect with the companys business and operations. This role will work with cross-functional partners across Resilience Global Technology and others across Nike. You will create data-driven insights and visualizations built on internal and external data sets. Our data products tell stories that reveal patterns and trends that enable effective decision making for our partners and stakeholders.

WHAT YOULL WORK ON

Developing and implementing statistical models and machine learning algorithms to analyze relevant structured and unstructured datasets and variables
Developing ML models and planning end-to-end ML model experiment design
Applying hypothesis testing regression A/B testing and time-series forecasting to product creation decisions and timelines
Working closely with innovation and engineering teams to build support and scale these data-driven insights to stakeholders across the enterprise
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 and methods
Monitor and troubleshoot data pipelines ensuring high availability and performance
Identify and tackle issues concerning data management to improve data quality
Design build and maintain robust ETL/ELT data pipelines reusable components frameworks and libraries to process data from various sources ensuring data quality and consistency

WHAT YOU BRING

Bachelors degree in Business Computer Science Finance Economics Statistics Engineering or a related field. We will accept any suitable combination of education experience and training.
5 years of progressive analytics and data visualization experience
3 years experience with Tableau
3 years of experience building models
3 years of deep learning neural network algorithm development
Expertise in languages like Python R and SQL for data manipulation analysis and model building
Experience in predictive analytics forecasting A/B testing complex modeling and data analysis
Proven experience developing and running simulation and optimization tools to support decision making
Ability to visualize data to tell stories that resonate with executive level stake holders.
Ability to communicate complex data in a simple actionable way to non-technical audiences
Experience with cloud tools for data science machine learning and modeling and visualization e.g. Jupyter Notebooks RStudio pandas PySpark SageMaker Databricks MLFlow Tableau PowerBI
Experience with ETL/ELT processes and data warehousing concepts
Excellent problem-solving skills and the ability to design solutions for complex data challenges

#LI-YR1

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.

Required Experience:

Exec

WHO WE ARE LOOKING FORWere looking for a Global Intelligence Analyst II to join the Data Analytics Intelligence team in the Nike Intelligence Center. Youll support data-driven decision-making across the enterprise by building and evaluating statistical and machine learning models designing experimen...

WHO WE ARE LOOKING FOR

WHO YOULL WORK WITH

WHAT YOULL WORK ON

Developing and implementing statistical models and machine learning algorithms to analyze relevant structured and unstructured datasets and variables
Developing ML models and planning end-to-end ML model experiment design
Applying hypothesis testing regression A/B testing and time-series forecasting to product creation decisions and timelines
Working closely with innovation and engineering teams to build support and scale these data-driven insights to stakeholders across the enterprise
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 and methods
Monitor and troubleshoot data pipelines ensuring high availability and performance
Identify and tackle issues concerning data management to improve data quality
Design build and maintain robust ETL/ELT data pipelines reusable components frameworks and libraries to process data from various sources ensuring data quality and consistency

WHAT YOU BRING

Bachelors degree in Business Computer Science Finance Economics Statistics Engineering or a related field. We will accept any suitable combination of education experience and training.
5 years of progressive analytics and data visualization experience
3 years experience with Tableau
3 years of experience building models
3 years of deep learning neural network algorithm development
Expertise in languages like Python R and SQL for data manipulation analysis and model building
Experience in predictive analytics forecasting A/B testing complex modeling and data analysis
Proven experience developing and running simulation and optimization tools to support decision making
Ability to visualize data to tell stories that resonate with executive level stake holders.
Ability to communicate complex data in a simple actionable way to non-technical audiences
Experience with cloud tools for data science machine learning and modeling and visualization e.g. Jupyter Notebooks RStudio pandas PySpark SageMaker Databricks MLFlow Tableau PowerBI
Experience with ETL/ELT processes and data warehousing concepts
Excellent problem-solving skills and the ability to design solutions for complex data challenges