Title: Senior Data Architect Location: Milwaukee, WI (Preference from Milwaukee, WI OR Nearby State who can travel) Duration: 6+ Months
Client develops retail merchandising solutions for global brands and retailers.
Using consumer insights and a retail science-based methodology, Client focuses on transportation, cosmetics, and consumer electronics industries.
The company specializes in retail environments, merchandising displays, digital merchandising, marketing programs, security solutions, and facility image products.
Client is seeking an experienced, highly motivated Data Architect who will support and maintain a state-of-the-art Analytics Center of Excellence using Snowflake SaaS services.
The ideal candidate is adept at using large data sets to find opportunities for product, process and metrics optimization and using models to test the effectiveness of different courses of action.
They must have strong experience using a variety of data mining/data analysis methods, using a variety of data tools, building and implementing models, using/creating algorithms and creating/running simulations.
They must have a proven ability to drive business results with their data-based insights.
They must be comfortable working with a wide range of clients, internal stakeholders and functional teams.
The right candidate will have a passion for discovering solutions hidden in large data sets and working with stakeholders to improve business outcomes.
Key Responsibilities / Functions:
Coordinate with various functional teams to implement models and monitor outcomes.
Monitor and analyze EDR data model performance and data accuracy.
Closely collaborate with the Analytics Center of Excellence to design, test and deploy data related solutions.
Mine and analyze data from databases to drive optimization and improvement of client programs, product development, marketing techniques and business strategies.
Effectively identify and communicate mined data patterns, metrics and KPIs to internal stakeholders.
Assess the effectiveness and accuracy of new data sources and data gathering techniques.
Provide input into custom data models and algorithms to apply to data sets.
Use predictive modeling to increase and optimize customer experiences, revenue generation, ad/content targeting and other business outcomes.