Data Analyst (On-site)

Newrez LLC•Coppell, TX

16h•Onsite

About The Position

The Data Analyst is responsible for participating in projects designed to improve operational performance and deliver excellent client service while assisting our internal operations units. The individual will leverage creative talents, excellent communication, analytic and project management skills. Be accountable for a designated group of operational departments or 3rd party clients by identifying and implementing new operational or client-based business strategies. Excel in a team-oriented, collaborative environment while contributing to the creation, design, and implementation of value-add business strategies that affect current operating practices and company policy. Be accountable for key operational risk-management metrics including investigating and coordinating the resolution of any operational issues that are discovered. Collect performance metrics for the monthly operational or client review and suggest new metrics. Exhibit strong communication and listening skills, focused on conveying new ideas to performance managers and understanding potential obstacles to implementation. Maintain a working knowledge of existing business processes and reporting. Retrieve data from the data warehouse structure. Perform query optimization and performance tuning. Be able to clearly articulate and present ideas and findings to a varied audience including the operations staff and senior management. Performs related duties as assigned by management. Conduct periodic data quality audits/surveys. Mine data to find behavioral patterns. Develop management reporting on findings and recommendations. May oversee testing and provide recommendations Other duties as assigned which may include: Uncover trends in customer campaign responsiveness to better segment the marketable population. Model and attribute pipeline pull through to prioritize more efficient leads and customer segments Ability to effectively and accurately convey information to others. Performs related duties as assigned by management.

Requirements

Bachelor’s Degree in an analytical or quantitative discipline, or related STEM field.
Two or more years of related experience as a data analyst in a financial setting.
Strong business communication skills with an ability to work well in a collaborative environment.
Strong attention to detail and an ability to multi-task, respond well to pressure and deadlines, and work well individually and in a collaborative environment.
Strong skills in Excel (graphs, pivot tables, formulas).
Experience visualizing data in Tableau/PowerBI/R/Python.
Strong skills in SQL programming.
Fast learner – able to assimilate new ideas and thrive in a fast-paced environment.
Must have smart phones that meet Company security standards with the ability to install apps such as Microsoft Authenticator.

Nice To Haves

Graduate degree preferred.
Prior work experience performing business, data, and/or statistical analysis is a plus.
Experience with PowerPoint and Visio a plus.
Natural entrepreneurial interest is a plus.

Responsibilities

Participating in projects designed to improve operational performance and deliver excellent client service while assisting our internal operations units.
Leveraging creative talents, excellent communication, analytic and project management skills.
Being accountable for a designated group of operational departments or 3rd party clients by identifying and implementing new operational or client-based business strategies.
Contributing to the creation, design, and implementation of value-add business strategies that affect current operating practices and company policy.
Being accountable for key operational risk-management metrics including investigating and coordinating the resolution of any operational issues that are discovered.
Collecting performance metrics for the monthly operational or client review and suggesting new metrics.
Maintaining a working knowledge of existing business processes and reporting.
Retrieving data from the data warehouse structure.
Performing query optimization and performance tuning.
Clearly articulating and presenting ideas and findings to a varied audience including the operations staff and senior management.
Conducting periodic data quality audits/surveys.
Mining data to find behavioral patterns.
Developing management reporting on findings and recommendations.
Overseeing testing and providing recommendations.
Uncovering trends in customer campaign responsiveness to better segment the marketable population.
Modeling and attributing pipeline pull through to prioritize more efficient leads and customer segments.