U.S. Citizens only — sponsorship is not available now or in the future
Must be currently based in (or willing to relocate to) Arizona before your start date
Looking for a Senior Data Scientist who's done this before — built it, broke it, fixed it, and knows exactly why each decision mattered.
This isn't a "here's a dataset, go build a model" role. You'll be trusted to architect ML solutions at scale, mentor other data scientists, and be the person stakeholders come to when they need a straight answer wrapped in a good story.
What you'll actually do:
- Design and deploy ML systems (forecasting, gradient boosting, deep learning) with real dollar impact — not academic exercises
- Build and maintain production pipelines using KubeFlow, Airflow, or Dataflow across cloud environments
- Use SHAP and model interpretability techniques to defend your model's decisions to non-technical execs
- Mentor junior data scientists and set the technical bar for the team
- Partner directly with engineering and product leadership to shape how ML gets used company-wide
What makes you a fit:
- PhD or Master's in Data Science, CS, Math, Engineering, or related quantitative field
- Deep hands-on experience with TensorFlow or PyTorch, Python, SQL
- Track record shipping models to production — not just prototyping
- Comfortable owning ambiguity and mentoring others through it
- Bonus: background in Finance, Quantitative Finance, or Economics — this combination tends to produce people who are both sharp with numbers and genuinely persuasive communicators
Setup:
Hybrid — 1 day/week onsite in Phoenix AZ
If 'I built it, it broke, I fixed it, and here's what I learned' is a sentence you can say more than once — this is your role.
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