Data Scientist Jobs in Miami.
All active Data Scientist roles based in Miami.
Pick a job to read the details
Tap any role on the left — its description and apply link will open here.
About the Role
This role will contribute to our broader valuation and pricing ecosystem and we’re looking for someone who can combine strong modeling intuition with hands-on execution and strong engineering to build practical solutions for a low-margin, high-stakes business where small improvements can have an outsized impact.
You’ll work on problems like modeling post-listing demand, estimating price elasticity, designing experiments, building structural models, and developing optimizers that help us make better decisions across our products and inventory.
We’re a small, nimble team, so there’s ample opportunity to shape both the modeling direction and how these systems get used in production decision-making.
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
• Background in real estate, housing, finance, or adjacent marketplace domains
• Familiarity with distributed data processing tools such as Pyspark
• Experience with machine learning methods broadly, including where deep learning can complement structured statistical modeling
• Experience working with large language models (LLMs) or vision-language models (VLMs)
What You'll Do
• Develop demand and conversion models using both pre-listing and post-listing signals
• Design and improve optimization frameworks that balance objectives like margin, conversion, and risk
• Apply statistical, econometric, and mathematical modeling techniques to problems where structure matters and pure black-box prediction is not enough
• Design experiments and measurement approaches to quantify price elasticity, customer response, and product trade-offs
• Partner with Engineering, Product, and Operations to turn models into systems that influence real decisions
• Bring a pragmatic, hands-on approach: move quickly from idea to prototype to production-ready scientific component
Compensation
Compensation
The base pay range for this position is $156,800-$335,000 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
Ready to apply?
Apply to Opendoor
Applied Scientist - ML/Ai
Share this job
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
Ready to apply?
Apply to Opendoor
About the Role
This role will contribute to our broader valuation and pricing ecosystem and we’re looking for someone who can combine strong modeling intuition with hands-on execution and strong engineering to build practical solutions for a low-margin, high-stakes business where small improvements can have an outsized impact.
You’ll work on problems like modeling post-listing demand, estimating price elasticity, designing experiments, building structural models, and developing optimizers that help us make better decisions across our products and inventory.
We’re a small, nimble team, so there’s ample opportunity to shape both the modeling direction and how these systems get used in production decision-making.
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
• Background in real estate, housing, finance, or adjacent marketplace domains
• Familiarity with distributed data processing tools such as Pyspark
• Experience with machine learning methods broadly, including where deep learning can complement structured statistical modeling
• Experience working with large language models (LLMs) or vision-language models (VLMs)
What You'll Do
• Develop demand and conversion models using both pre-listing and post-listing signals
• Design and improve optimization frameworks that balance objectives like margin, conversion, and risk
• Apply statistical, econometric, and mathematical modeling techniques to problems where structure matters and pure black-box prediction is not enough
• Design experiments and measurement approaches to quantify price elasticity, customer response, and product trade-offs
• Partner with Engineering, Product, and Operations to turn models into systems that influence real decisions
• Bring a pragmatic, hands-on approach: move quickly from idea to prototype to production-ready scientific component
Compensation
Ready to apply?
Apply to Opendoor
About the Role
This role will contribute to our broader valuation and pricing ecosystem and we’re looking for someone who can combine strong modeling intuition with hands-on execution and strong engineering to build practical solutions for a low-margin, high-stakes business where small improvements can have an outsized impact.
You’ll work on problems like modeling post-listing demand, estimating price elasticity, designing experiments, building structural models, and developing optimizers that help us make better decisions across our products and inventory.
We’re a small, nimble team, so there’s ample opportunity to shape both the modeling direction and how these systems get used in production decision-making.
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
• Background in real estate, housing, finance, or adjacent marketplace domains
• Familiarity with distributed data processing tools such as Pyspark
• Experience with machine learning methods broadly, including where deep learning can complement structured statistical modeling
• Experience working with large language models (LLMs) or vision-language models (VLMs)
What You'll Do
• Develop demand and conversion models using both pre-listing and post-listing signals
• Design and improve optimization frameworks that balance objectives like margin, conversion, and risk
• Apply statistical, econometric, and mathematical modeling techniques to problems where structure matters and pure black-box prediction is not enough
• Design experiments and measurement approaches to quantify price elasticity, customer response, and product trade-offs
• Partner with Engineering, Product, and Operations to turn models into systems that influence real decisions
• Bring a pragmatic, hands-on approach: move quickly from idea to prototype to production-ready scientific component
Compensation
Ready to apply?
Apply to Opendoor
Senior Exploitation Specialist/Data Scientist
Share this job
OVERVIEW
Streamline Defense is hiring a Senior Exploitation Specialist / Data Scientist to support the NGA mission at USSOUTHCOM. This role sits at the intersection of intelligence analysis and applied data science, turning large, complex datasets into operationally relevant insights for command planning and execution.
RESPONSIBILITIES
- Provide analysis and data science support across NGA intelligence missions
- Operate independently at a senior level within an SCI environment
- Build processes and pipelines around large datasets to surface analytic discoveries
- Develop visualizations that integrate cleanly into daily operations
- Operationalize analytic output by framing it to drive operational planning
REQUIREMENTS
- Active TS/SCI security clearance
- 10+ years of relevant experience. A combination of education, professional certifications, and training may be substituted in lieu of years of experience.
- Background providing analysis and/or data science in support of an intelligence mission
- Senior-level proficiency in Python scripting
- Proven ability to design processes around large datasets to identify analytic discoveries
- Working understanding of Transnational Criminal Organizations (TCOs) operating in the USSOUTHCOM AOR
- Familiarity with coca cultivation and production geography
- Working knowledge of ICD 203 (Analytic Standards) and ICD 206 (Sourcing Requirements)
ABOUT STREAMLINE
Streamline Defense is a Service-Disabled Veteran-Owned Small Business (SDVOSB) delivering professional and technical solutions across the Defense and Intelligence Enterprise. Our analysts, engineers, and cleared professionals support customers spanning the IC, U.S. Combatant Commands, and Military Services, contributing to some of the nation's most critical missions.
At Streamline, we foster a high-performance culture where driven professionals can grow, innovate, and make an impact. We provide an entrepreneurial environment where initiative is valued, expertise is rewarded, and contributions directly shape mission success. We offer competitive compensation, full benefits including health, dental, and vision, a 401k, and the kind of environment where your contributions are visible and your growth is real. This is the place to build your career if you are looking for meaningful work, top-tier colleagues, and the opportunity to make a real impact.
EQUAL EMPLOYMENT OPPORTUNITY (EEO) STATEMENT
Streamline is an equal-opportunity employer and is committed to hiring and retaining a diverse workforce. We recruit, hire, and promote based on qualifications, merit, and mission requirements, ensuring fair treatment for all employees and applicants. All employment decisions are made without regard to race, color, religion, sex, national origin, age, disability, veteran status, or any other characteristic protected by applicable federal, state, or local law.
Ready to apply?
Apply to Streamline Defense
About the Role
We are seeking an exceptional Senior Data Scientist to join our centralized Data organization. In this role, you will be embedded within our consumer and seller experience groups, working closely with cross-functional partners across product, engineering, design, and leadership. You will leverage data to generate deep insights that drive product strategy and create a world-class experience for our users. You'll work with terabytes of data to understand user behavior and directly impact customer satisfaction and business growth.
What You'll Do
- Develop and implement advanced analytics to drive product strategy and enhance the consumer and seller experience.
- Conduct deep-dive statistical analyses on large datasets to uncover user behavior insights and identify key business opportunities.
- Partner with product, engineering, and operations teams to identify opportunities to improve the user journey through data-driven insights.
- Design and execute A/B tests and other experiment types, like multi-armed bandit tests, to measure the impact of product changes and optimize the user experience.
- Build scalable data pipelines and reporting dashboards to deliver insights to stakeholders.
- Present findings and strategic recommendations to executive leadership.
- Contribute to the team and company knowledge base.
What You'll Need
- Advanced proficiency in SQL for complex data manipulation and analysis.
- Strong skills in Python for data analysis and visualization.
- Deep understanding of statistics, A/B testing, and experimental design.
- Excellent communication skills with the ability to present to executive leadership.
- Strong business intuition and the ability to translate technical findings into business recommendations.
- A self-motivated individual with a desire to solve complex, open-ended problems.
Education & Experience
Bachelor's degree or higher in a quantitative field such as Statistics, Economics, Mathematics, or Computer Science.
8+ years of experience in data science, product analytics, or a similar quantitative role.
3+ years of experience in e-commerce, two-sided marketplaces, or consumer-facing products preferred.
What We Offer
- Executive-level visibility with a direct impact on core business metrics.
- Opportunity to work on high-impact analytics projects that shape product strategy.
- Hybrid work model: 4 days in office, 1 day remote flexibility.
- Collaborative culture with cross-functional team integration.
- A fast-paced, high-growth environment with significant learning opportunities
Compensation
Our compensation plan consists of a base salary, Opendoor equity and a comprehensive package of benefits including paid time off, paid holidays, medical/dental/vision insurance, basic life insurance, and 401(k) to eligible employees. All compensation parameters are based on experience.
LI-RO
Ready to apply?
Apply to Opendoor
Data Scientist, Pricing
Location: In office 4 days a week; Ontario, Canada.
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.
Our compensation plan consists of a base salary, Opendoor equity and a comprehensive package of benefits including paid time off, paid holidays, medical/dental/vision insurance, basic life insurance, and 401(k) to eligible employees. All compensation parameters are based on experience.
#LI-RO
#LI-KC1
Ready to apply?
Apply to Opendoor
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.
Base salary range for this role varies. Generally, the base salary range is $186,000 – $256,000 annually + RSUs + ESPP + additional employee benefits (medical/dental/vision, life insurance, unlimited PTO, 401K).
#LI-RO
#
#LI-KC1
Ready to apply?
Apply to Opendoor