We innovate constantly to help the biggest names in business do business – quicker and smarter. It takes vision. It takes focus. And we apply both every bit as much to the way we do business too. The brightest minds, the latest technologies and pioneering processes are combining to enhance this critical business function at our Centre's for Excellence in Lake Mary, FL or Basking Ridge, NJ. We’re finding new ways to add value and provide strategic support. This is the kind of work we do. And you can be part of it .
This is a strategic reporting and analytical support role in the Verizon Credit & Fraud Governance organization, responsible for providing analytical insights to leadership for operational and strategic decision making. Responsibilities will include the use of data analysis and data mining expertise to support various projects using technical skills to conduct analytical and predictive modeling exercises.
Utilize advanced data mining and predictive modeling techniques to evaluate/ predict financial results and make recommendations to improve business decision-making.
Solve complex data-related questions by developing new predictive models and improving existing ones.
Analyze data from various sources to assess customer LTV as well as survival analysis models for monetization opportunities.
Hands-on review of data sets using SAS/R/Python, statistical analysis, and data visualization tools.
Perform credit and member base KPI management (A/R liquidation, attribution, revenue forecasting, model performance, customer value management, collection performance).
Perform business intelligence, data analysis, descriptive statistics and performance validation of existing and potential credit models.
Analyze and interpret data and build quantitative, non-linear, and time-series models using R/SAS/Python.
Determine modeling requirements in the development of standard data sets that will be used for analysis and data mining.
Participate in cross-functional project teams as modeling subject matter expert.
Research new modeling techniques as required to solve a given business problem.
An Associate´s degree in Finance, Mathematics, Statistics or related field, or equivalent work experience required. Strong mathematical, analytical, financial background and attention to detail.
Two or more years of experience with predictive modeling in R, SAS, and/or Python.
Ideally, you’ll also have:
A Bachelor’s degree in Finance, Mathematics, Statistics or related field.
Statistical forecasting and data mining techniques; demand pattern recognition, algorithm selection, outlier correction, parameter optimization.
Thorough knowledge of Linear/Logistic Regression and Decision Tree models.
Two or more years of experience in a data mining role with strong quantitative and analytical skills and a proven track record of turning large amounts of multi-faceted data into meaningful information.
Experience writing SQL against large Teradata and/or Oracle datasets….
Advanced knowledge of MS Excel and PowerPoint for data manipulation and report creation.
Previous use of Business Intelligence tools, such as Cognos, Business Objects, Tableau, Hyperion SSRS or others.
Effective communication skills in both written and verbal formats.
Demonstrated ability to work independently and in collaboration.
Proven ability to thrive in a dynamic environment and manage multiple projects simultaneously, adapt to changing priorities and meet deadlines.
Not to boast, but a little bit about us
Verizon powers America’s fastest and most reliable network. We’re also leading the way in cloud and security solutions, Internet of Things and video entertainment. Technology moves fast and so do we. We believe that bringing great ideas and customer experiences to life should be recognized and rewarded. Whether you think in code, words, pictures or numbers, find your future at Verizon.
Equal Employment Opportunity
We're proud to be an equal opportunity employer – and celebrate our employees' differences, regardless of race, color, religion, gender, sexual orientation, gender identity, national origin, age, disability, or Veteran status. Different makes us better.
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