BASIC FUNCTIONS:

Develops data-driven testing methodologies using LexisNexis data assets.

Clarifies and/or enhancing stakeholder understanding of test objectives and the data required to support the test.

Analyzes client data to prepare for analysis.  Identifies data quality concerns and opportunities (i.e. performance indicators, scores, approval/declination indicators, etc.) and clearly communicates these concerns to stakeholders along with suggestions for preventing these issues closer to project initiation.

Enforcing data quality testing best practices.

QUALIFICATIONS:

Bachelor's Degree holder.

Have 1-3 years’ experience in data manipulation, cleansing and modeling or equivalent demonstration of core skill set required to satisfy project requests.

Is comfortable working in a fast-paced environment.

Have excellent attention to detail, organization and documentation. 

Have expert oral and written communication skills, including the ability to describe analytical results to non-statistical audiences. 

TECHNICAL SKILLS:

Have experience in at least one general-purpose language (such as Python, Spark, R) required or equivalent analytic software.

Have experience with SQL and/or other database technologies.  

Have experience with using Git.

Is familiar with cloud-based tools (ex. Microsoft Azure or equivalent).

Able to quickly learn new technologies and programming languages.

ACCOUNTABILITIES:

Designing, testing, and/or executing automated file processing and data reporting workflows.

Executing database queries to extract and aggregate LN’s data assets into attributes and scores that are used for predictive modeling, reporting, and analysis.

Creating and enhancing the code and tools that support data processes.  Tools are easily usable by a wide audience, including teams outside of Data Science.

Creating and enhancing Python or Power BI-based reporting tools that allow team members to gain insights about LexisNexis data assets.

Performing all other duties as assigned.

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