Senior Data Scientist

About Phaedon

Phaedon is a leading loyalty partner for organizations across travel, hospitality, and retail, helping brands humanize loyalty by transforming customer interactions into meaningful, lasting relationships. Through innovative technology, strategic expertise, and advanced analytics, Phaedon delivers end-to-end loyalty solutions that generate measurable business outcomes. Its award-winning Tally™ platform enables organizations to scale loyalty with precision, deepen customer engagement, and strengthen connection at every stage of the relationship. Trusted by leading and growth-focused brands, Phaedon helps clients turn loyalty into a sustained driver of growth and long-term competitive advantage. Learn more at wearephaedon.com. 

About the Role:

We are looking for a Senior Data Scientist who is a builder, not just a maintainer. This is a high-ownership opportunity for an AI/ML engineer who wants to design and ship the models that power our loyalty platform in production, not just prototype them. You'll build AI/ML capabilities that our SaaS product calls at runtime: fraud detection, personalization, recommendation, and forecasting models served through APIs, not one-off notebooks handed to someone else to productionize.

We're looking for a self-starter who identifies opportunities to apply AI/ML to the product roadmap, proposes the approach, builds it, ships it, and owns it in production. The primary focus of this role is product-embedded model development.  There will be some client-facing work; however, it is anticipated to be a small portion of the role.  

Essential Duties/Responsibilities:

Product-Embedded Model Development (primary focus):

• Design, build, and own AI/ML models that are directly integrated into and called by our SaaS product in production

• Own the full model lifecycle: problem framing, data/feature design, training, evaluation, deployment as a callable service, and post-deploy monitoring/retraining

• Build and maintain production inference APIs and microservices that serve model predictions to the product with defined latency and reliability SLAs

• Implement and productionize models using AWS Bedrock, SageMaker, and other AWS AI services, going beyond POC into hardened, versioned, production systems

• Develop RAG (Retrieval-Augmented Generation) systems and other LLM-powered features as first-class product capabilities

• Proactively identify where AI/ML can create product differentiation (fraud detection, member behavior prediction, personalization/recommendation, anomaly detection) and bring proposals forward rather than waiting for requirements to be handed down

Cloud Infrastructure & MLOps:

• Build and manage SageMaker training pipelines, model registry, and endpoint deployments, including feature store integration and automated retraining triggers

• Build automation, monitoring, and alerting for production ML systems using Lambda and other AWS services

• Create and maintain Infrastructure-as-Code (Terraform, Pulumi, CloudFormation) for all model and pipeline infrastructure, no manual, undocumented deployments

• Build data pipelines that synthesize complex datasets from multiple sources into model-ready features

• Develop CI/CD pipelines for automated deployment and model versioning; implement model registry and rollback practices

• Implement error-proofing, integration testing, and monitoring/logging for AI systems running in production

Client & Cross-Functional Collaboration:

• Support select client engagements where deep technical model expertise is needed to scope or validate an AI/ML approach

• Partner with product and analytics leadership to translate roadmap priorities into shipped model capabilities

• When client-facing, present technical findings and recommendations with clarity to both technical and business stakeholders

Location:

This role is based out of our office in the Designer’s Guild building in the heart of Minneapolis' North Loop neighborhood.  We embrace a hybrid model with three in-office days per week to ensure a mix of collaboration and flexibility to support our employees' success.