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# PEGA Data Science and Analytics Specialist

- **Company:** Everforth Apex
- **Location:** Merrifield, VA, United States
- **Contract:** Temporary contract
- **Skills:** Computer Programming, Data Retrieval, Python (Programming Language), SQL Databases, Pega, Pyspark, Databricks
- **Published:** August 8, 2026
- **Apply:** https://www.dice.com/job-detail/2cfa5a21-da8a-4973-8d3b-1c4cf42fcc3e

## About the Role

Education: A Master's degree is required.

Experience: 5-10 years of professional experience, with 1-2 years of strong data science and coding experience.

Technical Skills:

 * Proficiency with Python/PySpark and SQL.
 * Familiarity with the Databricks environment.

Preferred Qualifications

 * Experience with Pega CDH is preferred.

## Description

We are seeking a PEGA Data Science and Analytics Specialist for a 6-9 month engagement. This role is focused on enabling and simplifying the analysis required for the faster implementation of new Customer Decision Hub (CDH) modeling features. The position involves creating libraries, standardizing data retrieval processes, and developing analytical notebooks to support various data science initiatives. The ideal candidate will have a strong background in data science, coding, and analytics., * Develop a library of required queries and scripts to replicate the CDH customer contextual object in external systems like Databricks for deeper analysis.

 * Standardize the format for executing key data retrieval steps for use by the broader team, including interaction to outcome attribution and model data to interaction mapping.
 * Create notebooks for the team to use for answering specific questions related to distribution, arbitration, and channel engagement analysis.
 * Support initial analysis for new model-related features, such as creating back-testing approaches, establishing baseline KPIs, and developing monitoring strategies.
 * Assist in on-going analysis, including model performance monitoring and ensuring NBI Program Model Health.
 * Address analytical gaps by standardizing analysis for actionable monitoring data and eligible audience monitoring.
 * Tie interactions back to key member demographic data for more granular analysis.


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