Jobs in United States › Applied Data Scientist / Machine Learning Engineer (Decision Intelligence)Applied Data Scientist / Machine Learning Engineer (Decision Intelligence) WorkWave · United States, US · Data
We are looking for a product-minded Applied Data Scientist or Machine Learning Engineer to help build, ship, and scale ML-powered products that directly improve how our customers make decisions, operate their businesses, and serve their own users.This is not a research-only role, nor is it a service-oriented internal analytics position. We want someone who has…
We are looking for a product-minded Applied Data Scientist or Machine Learning Engineer to help build, ship, and scale ML-powered products that directly improve how our customers make decisions, operate their businesses, and serve their own users.
This is not a research-only role, nor is it a service-oriented internal analytics position. We want someone who has taken machine learning from problem definition through experimentation, production deployment, measurement, iteration, and long-term ownership. You understand that great models are not just accurate in notebooks—they are usable, explainable, measurable, scalable, and valuable inside a real product.
Whether your background leans heavily toward Data Engineering/ML Ops or Applied Data Science, you have a strong bias toward shipping and an interest in bridging both worlds to bring AI to life.
WHAT YOU'LL DO:
Engineering & AI Enablement
End-to-End ML Ownership: Drive the development of machine learning capabilities (forecasting, recommendation, ranking, optimization, or decision intelligence) powering customer-facing SaaS products.
Pipeline & Model Development: Design reliable data and feature pipelines alongside models from discovery through experimentation, validation, deployment, and monitoring.
Product Integration: Partner with Product Managers and Software Engineers to embed ML directly into product workflows, user experiences, and decision-making tools.
Pragmatic Prototyping: Move quickly from prototype to production while balancing accuracy, interpretability, laten
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