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About the Role

We are seeking a Senior Data Scientist with a builder mentality to design and deploy AI/ML models powering our loyalty platform. This high-ownership role focuses on product-embedded model development, creating AI/ML capabilities for our SaaS product, including fraud detection, personalization, recommendation, and forecasting models served via APIs. You will proactively identify AI/ML opportunities, propose solutions, build them, and own them in production. While some client-facing work may be involved, the primary focus remains on product-embedded model development.

Responsibilities

Design, build, and own AI/ML models integrated into and called by our SaaS product in production.
Own the full model lifecycle: problem framing, data/feature design, training, evaluation, deployment, and post-deploy monitoring/retraining.
Build and maintain production inference APIs and microservices serving model predictions with defined SLAs.
Implement and productionize models using AWS Bedrock, SageMaker, and other AWS AI services.
Develop RAG (Retrieval-Augmented Generation) systems and other LLM-powered features.
Proactively identify AI/ML applications for product differentiation (e.g., fraud detection, member behavior prediction, personalization/recommendation, anomaly detection).
Build and manage SageMaker training pipelines, model registry, and endpoint deployments.
Build automation, monitoring, and alerting for production ML systems using AWS services.
Create and maintain Infrastructure-as-Code (Terraform, Pulumi, CloudFormation) for ML infrastructure.
Build data pipelines to synthesize complex datasets into model-ready features.
Develop CI/CD pipelines for automated deployment and model versioning.
Implement error-proofing, integration testing, and monitoring/logging for AI systems.
Support select client engagements requiring deep technical model expertise.
Partner with product and analytics leadership to translate roadmap priorities into model capabilities.
Present technical findings and recommendations to technical and business stakeholders when client-facing.

Requirements

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 systems OR equivalent combination of education and experience.
Demonstrated track record of taking a model from idea to production-serving endpoint inside a live product.
Fluency in the full model lifecycle: data/feature engineering, training, evaluation, deployment, versioning, monitoring, and retraining.
Knowledge of Infrastructure-as-Code (Terraform, Pulumi, CloudFormation) for deploying ML infrastructure.
Experience with source control and automated deployment pipelines (Git, Docker).
Demonstrated self-starter mindset: comfortable identifying product opportunities, scoping technical approaches, and driving to completion with minimal guidance.
Strong written and verbal communication skills.

Skills

Advanced Python (including AI/ML libraries like transformers, LangChain)
SQL
Boto3
AWS Bedrock
SageMaker
Prompt engineering
Model fine-tuning
AWS services (Bedrock, SageMaker, Lambda, Redshift, Athena, Glue)
Superset
Tableau
Power BI
Object-oriented programming
Testing frameworks
CI/CD
Model versioning
Vector databases
RAG implementations
API development
Microservices architecture

Location

Minneapolis, MN

Work Type

Hybrid

Experience Level

5+ years of hands-on experience building and shipping ML models into production systems

Education Level

Bachelor's degree in data science, computer science, computer engineering, or related field

Salary/Compensations

$105,000-155,000 per year

Benefits

Medical/dental/vision coverage
Comprehensive paid time off
Paid holidays
Paid parental leave
Retirement savings plans

About the Company

Phaedon is an equal opportunity employer.

Equal Opportunity

All employment decisions shall be made without regard to age, race, creed, color, religion, sex, national origin, ancestry, disability status, veteran status, sexual orientation, gender identity or expression, genetic information, marital status, citizenship status or any other basis as protected by federal, state, or local law.
Reasonable Accommodations are available, including, but not limited to, for disabled veterans, individuals with disabilities, and individuals with sincerely held religious beliefs, in all phases of the application and employment process.