Log Analytics Engineer

Duration: 6-month contract with possible extensions

Work Requirements: , Holders or Authorized to Work in the U.S.

PEGA Data Science & Analytics To enable and simplify analysis required for faster implementation of new CDH modeling features.

Looking for a candidate with 5-10 years of experience + Master's degree and 1-2 years of strong data science and coding experience.

Prioritized Deliverables:

• Library of required queries/scripts to replicate the CDH customer contextual object in external systems (databricks/asl) for deeper analysis
• Standardize format for executing key data retrieval steps for use by the broader team
• Interaction to outcome attribution (account opens)
• Model data to interaction mapping (model performance, predictor performance)
• Member Profile to interaction mapping
• Create notebooks for the broader team to use to answer specific questions
• Distribution Analysis
• Arbitration Analysis
• Channel Engagement Analysis

Skillset: The primary technical skills required would be familiarity with the databricks environment and proficiency with Python/PySpark and SQL. Pega CDH experience is preferred.

Some examples of the work as it directly relates to GEM

• Initial Analysis to Support New Model Related Features
• Propensity Thresholds
• Creating the back-testing approach (MDSA had no appetite at the time)
• Establishing baseline KPIs
• Creating the monitoring approach
• Initial Model Maturity Analysis (though Morgan's team is starting to be involved)
• Establishing baseline KPIs
• Gauging the impact of enabling the feature
• Creating the ongoing monitoring approach

On-going Analysis

• Model Performance Monitoring
• Though MDSA owns the code to run the notebooks, when changes must be made to the code GEM is heavily involved in creating the new logic
• NBI Program Model Health
• This exists in some form today, but it is not in a state that is readily available to be shared with leaders in O&A, MDSA, or broader Marketing

Broader O&A Analytical Gaps:

(Things Red, Sumant, and Tai typically scramble to create which should be readily available)

• "Actionable Monitoring Data:" Standardizing how we conduct this sort of analysis for consistency
• Capture when propensity scores are exceptionally low closer to real-time (1 day)
• Capture when actions are not providing value to their intended objective (acquisition, engagement)

Eligible Audience Monitoring

• Identifying Members eligible for different actions/treatments (simulation environment can help after going live to a certain extent)
• Tying interactions back to key Member demographic data for more granular analysis (this sort of analysis should be standardized so it can easily be done by all Members of O&A)

Our benefits package includes: Comprehensive medical benefits Competitive pay 401(k) retirement plan and much more!

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