Senior Data Scientist-Intelligent Assignment Engine (Hybrid)

About Rewards Network

For 41 years, Rewards Network has been helping restaurants grow revenue, increase traffic, and boost customer engagement through innovative financial, marketing services, and premier dining rewards programs. By offering unique card-linked offers, we introduce diners to fantastic restaurant experiences, leveraging advanced technology and data analytics to deliver value to restaurants, diners, and our strategic partners' loyalty programs.

Our Culture

At Rewards Network, you'll be part of a driven and diverse team that excels in collaboration, issue resolution, and taking ownership of both personal growth and the company's success. We take pride in partnering with the world's most powerful loyalty programs to drive full-price paying customers to local restaurants through marketing services and flexible funding options. Our engaging and rewarding environment is designed to help you gain your full potential.

Job Overview

We’re seeking a Senior Data Scientist with strong technical depth across data science, large-scale data pipelines, and production ML/data systems. Experienced leading the execution of complex data engineering and data science workstreams including batch pipelines processing hundreds of millions to billions of records, orchestration, customer segmentation, feature generation and management, and real-time or near-real-time assignment systems.

This role requires someone who is equally comfortable driving technical architecture decisions, defining and evolving data attributes and metrics, and bridging the gap between business stakeholders and the engineering and data teams. The right candidate will be able to operate as a technical lead and guide a team without formal management responsibility.

This is a hybrid position that requires in office presence 3 days a week (Tuesday-Thursday) in Chicago.

What you’ll bring to the table: (Responsibilities)

Short Term Specific

Oversee SLAs across the Intelligent Assignment Engine (IAE) pipeline (batch completion, feed delivery, attribute freshness, assignment turnaround) and drive activity-based classification and tiering of members and merchants, ensuring definitions, thresholds, and refresh cadences are aligned with business and downstream consumption needs.

Design and build the offer priority scoring framework used to rank eligible offers per member, including score definition, input features (member attributes, merchant attributes, behavioral signals, business priorities), weighting logic, and validation against business objectives, and evolve the scoring model as personalization and ML capabilities mature.

• Provide technical leadership and execution guidance across the IAE pipeline, including nightly batch assignment processing, member and merchant attribute management, eligibility evaluation logic, and S3-based data feed production
• Lead the design, generation, and ongoing management of customer segmentation and feature pipelines, including member group construction, attribute bucketing strategy, and the production of feature sets used for offer eligibility evaluation and targeting
• Lead the design and optimization of large-scale data processing workflows handling hundreds of millions to billions of records, including partitioning strategy, bulk ingestion, and performance tuning
• Own the evolution of the IAE attribute pipeline including member and merchant attribute design, metric definition, bucketing strategy, and ongoing quality validation, and drive alignment with business stakeholders on open decisions (tier boundaries, bucket values, time windows, metric design)
• Provide architectural guidance on the development of a real-time synchronous API layer for offer assignment, including near-real-time member enrollment and user-triggered assignment events, and ensure sound integration with the broader batch pipeline
• Oversee the analytics mart maintenance and incremental build-out post-MVP, ensuring data models remain accurate, performant, and aligned with evolving reporting needs
• Act as the primary technical bridge between business stakeholders (product, marketing, finance) and the IAE/data engineering team, translating business requirements into data pipeline and attribute requirements and translating data constraints back into business-legible terms
• Guide and review the work of junior data scientists and data engineers on the IAE team, providing technical direction and prioritization support without formal people management responsibility
• Collaborate with the Nova platform team and engineering to ensure IAE outputs meet downstream data contracts, S3 feed schemas, and serve the offer assignment pipeline reliably
• Define and maintain data contracts between IAE and downstream consumers (Nova, analytics marts, dashboards)
• Identify and surface data quality risks, pipeline gaps, and go-live readiness issues across IAE's attribute and assignment outputs
• Build and maintain documentation of IAE architecture, da