Data Analyst

We are seeking a Data Analyst that will be a part of an Analytics team that has been tasked with scoping, developing, modelling, implementing, and delivering robust statistical data analytics on payment data to identify and prevent potential fraudulent and improper payments.

Responsibilities:

Participate in the design, development, implementation, validation and use of analytical models and solutions (descriptive and eventually predictive models)
Perform complex, detailed data analysis with very granular level data while summarizing and presenting relevant findings to multiple levels of stakeholders
Create descriptive and predictive models to study patterns, trends, and likely outcomes while reporting findings to appropriate Agencies
Perform impact analysis to evaluate IT, data, and/or model changes while effectively communicating potential risks and effects to Agencies
Interpret complicated models, analytical techniques, and results to both technical and non-technical audiences of varying levels, including recommendations to reduce improper payments and fraudulent activity
Identify data quality issues and recommend the best course of action to address them
Create technical documentation, outlining design and technical specifications of models and analysis results
Research new analytical methodologies, tools, and data sets to further complement our existing framework

Qualifications:

Bachelors degree in Business, Finance, Economics, Computer Science or equivalent experience required
3+ years of experience in related field
Excellent analytical and problem solving skills with attention to detail and data accuracy
Strong interpersonal, communication (verbal and written), relationship management, and customer service skills with a focus on working effectively in a team environment
Experience dealing with analysing fraud and/or suspicious activity a plus
Proficiency in relational database management systems, spreadsheets, and analysis tools
Proficiency in data programming languages such as SQL, PostgreSQL, or PL/SQL
Proficiency in Microsoft Office Excel
Knowledge of analytical and statistical software packages such as SAS, R, Stata, Matlab, Eviews, or S-plus is desired
Ability to use Microsoft Office Suite (Word, PowerPoint, Access, Visio)
Strong organizational, time management, and follow up skills required
Ability to work cross-functionally to solve complex problems and improve quality and service
Ability to perform involved and independent research and analysis
Ability to present and convey results of analyses to various audiences
Ability to manage multiple projects and work processes in a timely fashion
Ability to maintain confidentiality and appropriately handle sensitive information