Machine Learning Researcher

Forty5Park; New York (NY); Remote; USD 87,000 - 148,000; Full time

Job summary

Join an innovative startup at the forefront of AI in institutional real estate underwriting. As a Machine Learning Researcher, you will shape our platform's analytical capabilities, developing advanced forecasting methods and collaborating closely with our leadership team. Bring your industry experience to drive research that directly impacts our client outcomes.

Benefits

Competitive salary and equity

Opportunity to shape R&D direction

Collaborative work environment

Qualifications

• 5–7+ years of industry experience in machine learning or forecasting.
• Strong Python skills and hands-on experience with ML libraries.
• Deep experience in forecasting and tuning ML models.

Responsibilities

• Research and refine novel ML algorithms, especially in forecasting.
• Collaborate with the Chief Data Scientist for new model architectures.
• Contribute to internal research and affect client outcomes.

Skills

Python

Machine Learning

Time Series Analysis

Forecasting

Probabilistic Programming

Education

PhD in a quantitative field

Tools

scikit-learn

NumPy

pandas

PyTorch

TensorFlow

Job description

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We are an early-stage startup building a next-generation AI platform for institutional real estate underwriting. Our platform empowers investors and operators to scale acquisitions through advanced forecasting, AI-augmented decision-making, and cutting-edge machine learning research. We're looking for a curious, driven, and inventive Machine Learning Researcher to help us rethink how complex real estate deals are evaluated at scale.

This is a research-first role, not focused on ML infrastructure or traditional engineering. Your work will shape the analytical brain of our platform—developing novel forecasting methods, fine-tuning probabilistic and deep learning models, and bringing original R&D ideas from whiteboard to proof-of-concept alongside the Chief Data Scientist.

Location: Remote or New York City

Type: Full-time

About Us:

We are an early-stage startup building a next-generation AI platform for institutional real estate underwriting. Our platform empowers investors and operators to scale acquisitions through advanced forecasting, AI-augmented decision-making, and cutting-edge machine learning research. We're looking for a curious, driven, and inventive Machine Learning Researcher to help us rethink how complex real estate deals are evaluated at scale.

This is a research-first role, not focused on ML infrastructure or traditional engineering. Your work will shape the analytical brain of our platform—developing novel forecasting methods, fine-tuning probabilistic and deep learning models, and bringing original R&D ideas from whiteboard to proof-of-concept alongside the Chief Data Scientist.

What You'll Do:

• Research, prototype, and refine novel ML algorithms—particularly in time series forecasting, Bayesian modeling, and deep learning
• Improve the accuracy, robustness, and interpretability of existing models used in underwriting workflows
• Collaborate directly with the Chief Data Scientist to ideate and test new model architectures and inference methods
• Publish internal research, run experiments, and contribute to our roadmap for model-driven underwriting
• Interface with cross-functional teams to translate research into platform capabilities that impact client outcomes and revenue

Qualifications

Required:

• 5–7+ years of industry experience in machine learning, forecasting, or applied statistics
• OR
• 3–5+ years of experience with a PhD in a quantitative field (e.g., Computer Science, Statistics, Physics, Engineering, Finance)
• Strong Python skills and hands-on experience with ML libraries (e.g., scikit-learn, NumPy, pandas, PyTorch, TensorFlow)
• Deep experience in forecasting, time series analysis, and tuning ML models for performance
• Proven track record of leading or significantly contributing to R&D initiatives
• Strong ability to think theoretically while also delivering practical, testable model implementations

Preferred:

• Proficiency in Bayesian methods and probabilistic programming (e.g., PyMC, NumPyro, Stan)
• Background in real estate, finance, econometrics, or decision-based systems
• Familiarity with uncertainty modeling and explainable ML techniques

Why Join Us

• Join at the ground floor of a stealth AI startup with real-world use cases and institutional traction
• Drive original ML research with immediate, measurable business impact
• Collaborate closely with leadership in a low-bureaucracy, high-impact environment
• Competitive salary, equity, and the opportunity to shape the direction of our R&D

Seniority level

• Seniority level

  Mid-Senior level

Employment type

• Employment type

  Full-time

• Industries

  Technology, Information and Internet

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