Senior Data Scientist

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, Phaedonhelps clients turn loyalty into a sustained driver of growth and long-term competitive advantage.

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We are looking for aSenior Data Scientist who is abuilder, 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'llbuildAI/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 product ionize.

We'relooking for a self-starter whoidentifiesopportunities 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 isanticipatedto be a smallportionof the role.

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 andmaintainproduction inference APIs and microservices that serve model predictions to the product with defined latency and reliability SLAs
• Implement and product ionize models using AWS Bedrock, Sage Maker, 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
• Proactivelyidentifywhere 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
• Build and manage Sage Maker 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, Cloud Formation) 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:

• Supportselectclient engagements where deep technical modelexpertiseis needed to scope orvalidatean 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

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.

• Bachelor's degree in data science, computer science, computer engineering, or related field AND 5 + years of hands on experience building and shipping ML models into production systemsORequivalent combination of…