Sr. Marketing Measurement Analyst (Remote)

Belk•Charlotte, NC

2d•$90,000 - $132,000•Remote

About The Position

Sr. Marketing Measurement Analyst is reporting to the Director of Customer Analytics and is responsible for broad range of analytics used in establishing customer strategies and providing valuable customer-centric data insights for cross-functional audience including Merchandising, Marketing and Supply Chain. In this role candidate will build out and automate reports & dashboards, extract data from multiple sources to build models/algorithms used to fine-tune customer strategies, and build more advanced AI/machine learning tools and processes. The person in this role must possess strong data analytical skills and technical skills used in data engineering (mining from multiple sources/systems), predictive scenario modeling and machine learning knowledge. Analytics & Data engineering: Automating reports, dashboards, and other performance tools Data engineering/mining (collecting, transforming, cleansing and analyzing) Providing valuable business analytics and insights out of data samples thru hypothesis testing Utilizing different databases and connections and 3rd party data sets to enhance analytics scope Building data visualizations in Tableau, R-Shiny or other Providing ad-hoc analysis and presenting results in a clear manner AI/Machine Learning & Programing: Building AI/machine learning tools to optimize analytics and processes within the company Applying statistical methods and building machine learning algorithms (such as k-NN, Naive Bayes, SVM, Decision Forests) Using query languages such as SQL Utilizing data science toolkits such as R and Python (excellence in at least one of these) Maintaining expert-level knowledge on data science trends, technologies, and methodologies Scoring of key attributes used in deep statistical analysis and modeling Leading in defining the project methodologies and approach Other skills: Data affinity with attention to detail Solution and problem-solving oriented Strong Communication Skills (ability to communicate complex data in a simple way) Strong Presentation Skills and Technical Writing Skills Ability to work within a diverse background team or independently Able to quickly interpret the data and transition it into tangible business recommendation

Requirements

Bachelor's Degree in data science, statistics, computer science, business or related field, require
Strong analytical and data wrangling skills allowing to move quickly through large volumes of data
Aggressive in pursuing opportunities and focused on providing technical and analytical business solutions to drive store level results
Creative thinker focused of problem solving, finding efficiencies and streamlining processes
Strong communicator with ability to work in group environment
Flexible and adaptable, team-player able to work in a dynamic group environment
Passionate for coaching and development of talent
Ability to manage time and workload effectively with flexibility to shift focus/priorities at a moment's notice
An ability to influence cross-functionally across a wide range of business areas and levels
Excellent written and verbal communication skills
Proven success in using data-driven analysis to assess opportunities and drive results
Data affinity with attention to detail
Solution and problem-solving oriented
Strong Communication Skills (ability to communicate complex data in a simple way)
Strong Presentation Skills and Technical Writing Skills
Ability to work within a diverse background team or independently
Able to quickly interpret the data and transition it into tangible business recommendation

Responsibilities

Automating reports, dashboards, and other performance tools
Data engineering/mining (collecting, transforming, cleansing and analyzing)
Providing valuable business analytics and insights out of data samples thru hypothesis testing
Utilizing different databases and connections and 3rd party data sets to enhance analytics scope
Building data visualizations in Tableau, R-Shiny or other
Providing ad-hoc analysis and presenting results in a clear manner
Building AI/machine learning tools to optimize analytics and processes within the company
Applying statistical methods and building machine learning algorithms (such as k-NN, Naive Bayes, SVM, Decision Forests)
Using query languages such as SQL
Utilizing data science toolkits such as R and Python (excellence in at least one of these)
Maintaining expert-level knowledge on data science trends, technologies, and methodologies
Scoring of key attributes used in deep statistical analysis and modeling
Leading in defining the project methodologies and approach