Data Scientist

Opendoor; Seattle (WA); Hybrid; USD 140,000 - 190,000; Full time

Job summary

Opendoor in Seattle seeks a data scientist focused on pricing to help price real estate at scale. You will build pricing metrics, run experiments, and develop predictive models that influence margin, risk, and customer trust.

You will partner with Product, Engineering, and Operations to deploy models, interpret results, and communicate insights to executives. This role blends economics, ML, and product strategy in a fast-paced marketplace.

Qualifications

• Strong statistical reasoning for experimental design and causal inference.
• End-to-end ML ownership from data collection to deployment and monitoring.
• SQL and Python proficient; comfortable with production data pipelines and ML tools.
• Ability to translate analyses into actionable business recommendations.
• Experience tackling ill-defined problems and defining success metrics.

Responsibilities

• Build and maintain pricing metrics, dashboards, and frameworks.
• Run experiments and causal analyses to measure impact and inform decisions.
• Develop predictive and statistical models to improve pricing accuracy.
• Collaborate with Product, Engineering, and Operations to deploy models.
• Deliver insights that inform executive strategy.

Skills

Statistical reasoning

ML ownership

SQL + Python

Communication skills

Data product experience

Tools

Spark

Airflow

Ray

SageMaker

Vertex

Job description

About Opendoor

At Opendoor our mission is to tilt the world in favor of homeowners and those who aim to become one. Homeownership matters. It's how people build wealth, stability, and community. It's how families put down roots, how neighborhoods strengthen, how the future gets built. We're building the modern system of homeownership giving people the freedom to buy and sell on their own terms. We’ve built an end-to-end online experience that has already helped thousands of people and we’re just getting started.

Data Scientist, Pricing

Location: Hyrbrid 4 onsite, 1 remote Seattle WA.

Opendoor is transforming one of the largest, most complex markets in the world — residential real estate — using data at massive scale. Every pricing signal we generate directly impacts how we value homes, how we manage risk, and how efficiently capital moves through our marketplace. The work is highly leveraged: the quality of our pricing decisions influences conversion, margins, customer trust, and the company’s financial performance.

We are looking for mid to senior level Data Scientists. In this role, you will be a core driver of how Opendoor prices real estate at scale. You’ll operate at the intersection of economics, machine learning, experimentation, and product strategy — tackling ambiguity, shaping the pricing roadmap, and building models/analyses that materially move the business. Your insights will influence how we evaluate millions of dollars of housing inventory — and directly shape outcomes for our customers, our balance sheet, and the health of our marketplace.

What You’ll Do

• Build and maintain pricing metrics, dashboards, and frameworks.
• Run experiments and causal analyses to measure impact and drive decisions.
• Develop predictive + statistical models that improve pricing accuracy.
• Partner closely with Product, Engineering, and Operations teams to influence roadmap and model deployment.
• Deliver insights and narratives that inform executive strategy.

Skills & Qualifications

• Deep statistical reasoning: hypothesis design, experimental design, causal inference, and ability to distinguish signal vs noise.
• Proven end-to-end ML ownership: data acquisition, feature engineering, model development, validation, deployment, and ongoing monitoring.
• Strong SQL + Python proficiency; comfortable working with production data pipelines and modern ML tooling (e.g., Spark, Airflow, Ray, SageMaker, Vertex, etc.).
• Demonstrated ability to translate complex analytical findings into clear business recommendations and influence cross-functional decision-making.
• Experience working with ill-defined problems and driving clarity on problem definition, success metrics, and realistic tradeoffs.
• High data-quality bar: disciplined approach to validation, bias analysis, and making decisions rooted in evidence vs intuition.
• Effective communicator — able to tell the story behind the model to both highly technical and non-technical audiences.
• 8+ years of experience in data science, product analytics, or a similar quantitative role.