Lead Data Scientist

Summary:

We are seeking an experienced Lead Data Scientist to drive AI, Machine Learning, Predictive Analytics, and Intelligent Automation initiatives across the Rewards organization. This role will identify high-value AI opportunities, develop scalable analytical solutions, and translate complex data into actionable business insights that improve customer engagement, operational efficiency, and program performance. The ideal candidate combines strong technical expertise with business acumen and will work closely with Product, Engineering, Operations, and Business teams to deliver innovative AI solutions while establishing reusable frameworks, standards, and best practices for future adoption.

Responsibilities:

• AI & Advanced Analytics:
  • Identify, evaluate, and prioritize AI opportunities across Rewards products and operations.
  • Design and develop machine learning, predictive analytics, and optimization solutions for business challenges.
  • Build models for customer behavior prediction, segmentation, propensity scoring, forecasting, and recommendation engines.
  • Develop anomaly detection solutions to proactively identify operational, transactional, and program-related issues.
• Generative AI & Intelligent Automation:
  • Explore and implement Generative AI, Agentic AI, and workflow automation use cases.
  • Develop AI-powered assistants, knowledge discovery solutions, and decision-support tools.
  • Partner with engineering teams to operationalize AI solutions at scale.
• Data Science Delivery:
  • Lead end-to-end model development including data exploration, feature engineering, training, validation, deployment, and monitoring.
  • Ensure AI solutions are scalable, explainable, measurable, and aligned with business objectives.
  • Drive experimentation and continuous improvement through data-driven decision making.
• Documentation & Knowledge Enablement:
  • Create comprehensive documentation for AI models, analytical frameworks, methodologies, and solutions.
  • Develop AI playbooks, implementation guides, reusable templates, and best practices.
  • Contribute to Rewards AI standards, governance frameworks, and reference architectures.
  • Conduct knowledge-sharing sessions and provide guidance to engineering and business teams.
• Stakeholder Engagement:
  • Collaborate with business leaders to identify opportunities and define success metrics.
  • Present insights, recommendations, and outcomes to senior leadership.
  • Act as an AI subject matter expert and trusted advisor for strategic initiatives.

Requirements:

• Master's or PhD in Data Science, Computer Science, Statistics, Mathematics, or related field.
• 19 years of experience in Data Science, Machine Learning, AI, or Advanced Analytics.
• Strong proficiency in Python, SQL, and modern machine learning frameworks.
• Experience developing production-grade AI/ML solutions.
• Strong understanding of predictive modeling, anomaly detection, segmentation, forecasting, and statistical analysis.
• Experience working with large-scale transactional and customer data.

Key Skills:

• Artificial Intelligence
• Machine Learning
• Predictive Analytics
• Generative AI
• Anomaly Detection
• Customer Segmentation
• Forecasting
• Recommendation Systems
• Python
• SQL
• Databricks
• Azure AI
• MLOps
• Data Visualization
• Stakeholder Management
• Technical Documentation
• AI Governance

Preferred Skills:

• Experience in Loyalty, Rewards, Payments, Financial Services, or Customer Engagement platforms.
• Hands-on experience with:
  • Azure AI / Azure OpenAI
  • Databricks
  • Snowflake
  • Spark / PySpark
  • TensorFlow, PyTorch, Scikit-Learn
  • Generative AI and Agent-based frameworks
• Knowledge of MLOps, Model Governance, and Responsible AI practices.

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