Pega Decisioning Consultant (6-15 yrs)

Job Description :

We are looking for a skilled Pega Decisioning Consultant/Architect to design, develop, and implement Pega Customer Decision Hub (CDH) solutions that enhance customer engagement and decision-making processes. The ideal candidate will have expertise in Pega Decisioning, Next-Best-Action (NBA), Predictive & Adaptive Analytics, and real-time decisioning strategies.

Key Responsibilities :

- Design and implement Pega Customer Decision Hub (CDH) solutions for real-time decisioning and Next-Best-Action (NBA) strategies.

- Develop decisioning strategies, engagement policies, and predictive models to improve customer interactions.

- Collaborate with business stakeholders, data scientists, and developers to define customer-centric decisioning solutions.

- Configure and optimize Pega Adaptive Decisioning and Predictive Analytics models for personalized recommendations.

- Integrate Pega Decisioning with enterprise systems, marketing platforms, and data sources.

- Ensure Pega best practices, governance, and compliance are followed in decisioning implementations.

- Troubleshoot and resolve technical issues related to decision strategies, data flows, and real-time execution.

- Stay updated with Pega releases, AI-driven decisioning trends, and industry best practices.

Requirements :

- Bachelor's/Master's degree in Computer Science, Information Technology, or related field.

- 5+ years of experience in Pega, with at least 3+ years in Pega Decisioning/CDH.

- Pega Certified Decisioning Consultant (PCDC) certification is highly preferred.

- Strong experience in Next-Best-Action, Engagement Policies, and AI-powered Decisioning.

- Hands-on experience with Pega Strategies, Adaptive & Predictive Analytics, and Data Flows.

- Knowledge of Pega Marketing, NBA Designer, and Customer Journeys.

- Experience with REST APIs, data integration, and real-time decisioning architectures.

- Strong analytical, problem-solving, and communication skills.

Nice-to-Have :

- Experience with AI/ML models, data science concepts, and customer analytics.

- Exposure to cloud platforms (AWS, Azure, GCP) and data lakes.

- Prior experience in Banking, Insurance, Retail, or Telecom industries."