Equifax empowers businesses and consumers with information they can trust. With a strong heritage of innovation and leadership, we leverage our unique data, advanced analytics and proprietary technology to enrich the performance of businesses and the lives of consumers.
Equifax is looking for a Data Scientist to join our World-Class Global Sourcing and Procurement team. In this role the potential candidate will be responsible for delivering insights on company spend for the Global Sourcing and Procurement teams.
The core data analytics will be focused on the Global Sourcing and Procurement function which could include : Analytics related to overall company spend, analyzing our supplier base, analysis related to our transactions and analytics related to our industry or trends.
In addition, analytics that can be used to improve our sourcing processes will be highly valued in this role.
This role will interact directly with Information Technology (IT), Business Intelligence and Analytics, Sourcing teams, and internal affiliates to deliver innovative, insightful, and actionable results This role is responsible for conceptualizing and executing qualitative and quantitative projects and analyses to help drive data-based decision making in the sourcing and procurement space.
The ideal candidate must be able to able to build relationships across all levels of the organization and is recognized as a problem solver that looks to elevate the work of everyone around them.
Basic Requirements :
Must be fluent in English
Bachelor’s Degree (Science, Math or Engineering desirable)
Minimum of 5 years work experience or at least 3 years Sourcing or Procurement experience Knowledge and proficiency with Oracle, Oracle Spend Analytics and other management and financial information systems
SQL skills, ability to perform effective querying involving multiple tables and subqueries
Experience with data visualization tools : Tableau, Raw, Spotfire, Power BI.Google Charts, D3.js, etc.
Proficiency in Microsoft applications, including Excel, Access, Word, and PowerPoint
C, C++, Python, or other programming languages
Experience with big data tools : Teradata, Aster, Hadoop, Hive, etc.
Excellent communication, collaboration and delegation skills
Strong problem solving, quantitative and analytical abilities
Comfortable with ambiguity and ability to work through vague requirements with minimal oversight and process
Strong oral and written communication skills, and ability to collaborate with cross-functional partners
Preferred Requirements :
Thorough understanding of Machine Learning (ML) & Artificial Intelligence (AI), and real world practical application of such technologies
RPA experience (UiPath)
Working knowledge of data mining principles : predictive analytics, mapping, collecting data from multiple data systems on premises and cloud-based data sources
Understanding of and experience using analytical concepts and statistical techniques : hypothesis development, designing tests / experiments, analyzing data, drawing conclusions, and developing actionable recommendations for business units
Knowledge of statistical modeling techniques : GLM multiple regression, logistic regression, log-linear regression, variable selection, etc.