Senior Data Scientist (MLE)

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Stealth AI Startup
165000 - 210000 USD / Year
  • Engineering
  • FullTime
  • Applications have closed

Senior Data Scientist / Statistician — AI for Real Estate (NYC Hybrid)

We’re building the intelligence layer for one of the world’s largest industries — real estate — and we’re looking for a Senior Data Scientist who’s equally excited about cutting-edge ML research and shipping models to production.

If you love combining Bayesian reasoning, causal inference, and neural networks to explain and predict real-world behavior, this might be your kind of playground.

What You’ll Work On

  • Experiment with large-scale ML models that power dynamic property insights and risk prediction.
  • Design causal frameworks and statistical experiments to separate signal from noise in complex markets.
  • Launch Python models into production (PyTorch preferred), collaborating closely with engineers and product leaders.
  • Prototype new modeling ideas — from Monte Carlo simulations to Bayesian networks — and turn them into measurable business impact.
  • Communicate insights to both technical and non-technical audiences through clear storytelling and visualization.

What We’re Looking For

  • Hands-on MLE experience: you’ve deployed ML models to production and understand real-world constraints.
  • Deep stats background — you’re comfortable with Bayesian inference, probabilistic programming, and experiment design.
  • Strong Python skills (PyTorch, NumPy, Pandas) and solid software fundamentals (Git, Linux, testing).
  • Curiosity that spans ML, statistics, and product thinking. You want to see your models drive decisions, not just metrics.
  • (Bonus) Graduate degree in a quantitative field (Stats, Math, EE, Economics, Operations Research).

Why You’ll Love It

You’ll join a small, senior team of builders using machine learning to make real-world assets smarter. The environment is fast-paced, product-driven, and deeply technical — ideal for someone who wants both autonomy and impact.

📍 Hybrid in New York City (3x per week onsite). Competitive comp, real ownership, and the chance to shape the early ML foundation of a category-defining product.