About the Role

What You'll Need

• Experience developing quantitative models to support real-world decision-making under uncertainty
• Strong coding skills in Python, with the ability to move beyond prototyping and implement production-quality scientific code
• Experience with one or more of the following: causal inference, Bayesian modeling, structural modeling, demand forecasting, pricing science, or mathematical optimization
• Comfort working with messy, high-dimensional real-world data and translating ambiguous business problems into rigorous modeling approaches
• Advanced degree (MS or PhD preferred) in statistics, mathematics, economics, operations research, computer science, or another quantitative discipline
• Strong communication and collaboration skills — you’re comfortable working with cross-functional stakeholders and can communicate technical ideas clearly

Nice to Have

What You'll Do

Compensation

About the Role

We’re looking for an Applied Scientist (ALL LEVELS) to push the boundaries of applied machine learning and AI at Opendoor. While this role will have a significant impact on our valuation systems — ensuring we provide the most accurate and transparent pricing possible — the scope goes well beyond pricing. You’ll work across a range of challenging ML problems, from multi-modal modeling to operational optimization, helping us rethink how we use structured and unstructured data to make better decisions for our customers.

What You'll Need

• Strong software engineering and coding skills in Python, with experience contributing to production codebases
  
  
• Experience developing and deploying ML models end-to-end — from research and prototyping to implementation in production systems
  
  
• Hands-on experience with deep learning architectures, including ConvNets, Transformers, or similar
  
  
• Advanced degree (MS or PhD) in computer science, statistics, mathematics, or a related quantitative field
  
  
• Solid foundation in statistics and experimental design
  
  
• Strong communication and collaboration skills — you’re comfortable working with cross-functional stakeholders and can communicate technical ideas clearly
  
  

Nice to Have

• Familiarity with Pyspark and distributed data processing
  
  
• Background in search, recommendation systems, or personalization
  
  
• Experience working with large language models (LLMs) or vision-language models (VLMs)
  
  
• A genuine interest in real estate — no prior experience required, but you'll engage deeply with housing data
  
  

What You'll Do

• Design and deploy architectural improvements to our deep neural network (DNN)-based home valuation models
  
  
• Build interpretable ML models that can help us explain pricing decisions to customers
  
  
• Incorporate unstructured data — like images, videos, or text — into our forecasting and valuation pipelines using cutting-edge AI models (LLMs, VLMs, etc.)
  
  
• Collaborate with Engineering and Ops to enhance our human-in-the-loop pricing systems
  
  
• Improve the feature engineering and model training pipelines that power our production systems
  
  
• Rethink our risk and optimization models using real-world data and domain insight
  
  

We’re a small, nimble team — there’s ample opportunity to work across the entire research and modeling stack.

Compensation

The base pay range for this position is $156,800-$310,000 annually, plus RSUs. Pay within this range varies by work location and may also depend on your qualifications, job-related knowledge, skills, and experience. We also offer a comprehensive package of benefits including unlimited PTO, medical/dental/vision insurance, life insurance, and 401(k) to eligible employees.

#LI-RO

What You'll Be Owning:

We are seeking a highly skilled Senior Data Scientist to support mission-critical intelligence operations. The ideal candidate brings deep analytic expertise, advanced data science capabilities, and demonstrated experience supporting national security objectives across GEOINT, multi-INT, and enterprise-level analytic environments. This position requires the ability to innovate, modernize analytical tradecraft, and drive the integration of advanced methodologies into customer mission sets.

What You Must Have: 

• Active TS/SCI Clearance is required with the ability to obtain a CI Poly 10+ years of relevant experience. (A combination of years of experience & professional certifications/trainings can be used in lieu of years of experience)
• Expertise in advanced analytic methodologies and proven ability to implement them to increase customer satisfaction and mission effectiveness.
• Proven Intelligence Community experience working with integrated teams and applying documented analytic methodologies to answer complex intelligence questions.
• Experience in data mining, database manipulation, and maintaining structured analytic datasets.
• Demonstrated proficiency using analytic tools to modernize workflows and enhance analytic rigor.
• Experience with Python/R scientific computing libraries (NumPy, Pandas, etc.)
• Experience applying machine learning or statistical modeling techniques (e.g., regression, clustering, classification, time-series analysis) to mission datasets.
• Proficiency in data preprocessing, feature engineering, and preparing structured/unstructured datasets for advanced analysis.
• Ability to evaluate model performance, conduct error analysis, and effectively communicate model results to both technical and non-technical audiences.
• Experience operationalizing analytic models into repeatable pipelines supporting intelligence production at scale.
• Understanding of modern data science best practices, including model governance, reproducibility, transparency, and lifecycle management.
• GEOINT / Multi-INT Core Tradecraft Support GEOINT analysis using imagery, spatio-temporal datasets, and multi-source intelligence to uncover relationships, trends, and mission-relevant events.
• Conduct multi-INT research to augment imagery analysis and provide mission-specific context.
• Demonstrated ability to lead technical and analytical teams in solving complex intelligence problems.
• Experience developing new geospatial tradecraft, methods, and technologies from an operations research perspective.
• Ability to identify system enhancements, capability gaps, new technologies, and business case opportunities that strengthen mission delivery.

What Would Be Nice to Have:

• Experience building and maintaining GEOINT, SIGINT, or OSINT datasets aligned to mission requirements.
• Ability to design and deliver briefings, demonstrations, and training events for users at all skill levels across mission applications.
• Experience supporting DoD and IC report production, briefings, and formal analytic publications.
• Ability to extract, model, and visualize multi-INT datasets for both descriptive and predictive analysis.
• Hands-on experience working with FADE tools (MIST, INTELBOOK, LINX, WATCH BOX) to discover and refine analytical insights.
• Proficiency with statistical and visualization tools (e.g., Tableau, MATLAB, Brewlytics, JEMA, MapLarge) for advanced statistical analysis and visualization of large datasets.
• Knowledge of Structured Observation Management tools and/or Object-Based Production methodologies.
• Experience in applying deep learning or computer vision techniques (e.g., CNNs, segmentation, object detection) to GEOINT or multi-INT datasets.
• Familiarity with distributed analytics frameworks such as Spark, Dask, or Ray. Experience building analytic dashboards or applications using frameworks.
• Experience with API-driven ingestion, ETL pipelines, or microservice-based analytic architectures.
• An understanding of Transnational Criminal Organizations (TCOs) operating within the USSOUTHCOM AOR
• An understanding of coca cultivation and production areas Familiarity with Intelligence Community Directive (ICD) 203 (Analytic Standards) and ICD 206
• An understanding of how to operationalize the analytic output—shape/frame it in a way that supports operational planning

#LI-GM1