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

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 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

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

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#LI-KC1

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

What You’ll Be Owning:

We are seeking a senior-level Data Scientist to design, develop, and deploy advanced data-driven applications in support of mission-critical environments. The ideal candidate operates independently with minimal oversight, delivers production-grade solutions, and understands how to translate operational requirements into scalable, secure solutions.

This role blends full-stack Python development, geospatial analytics, dashboarding, DevSecOps practices, and familiarity with Intelligence Community (IC) and DoD environments.

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 & education can be used in lieu of years of experience)
• Expert-level proficiency in Python and demonstrated experience building scalable, production-ready applications.
• Experience querying and integrating web APIs to retrieve, normalize, and operationalize data.
• Proficiency with at least one Python web framework (Flask, FastAPI, Django, or similar).
• Experience developing interactive data visualizations using Plotly, Seaborn, Matplotlib, Bokeh, or comparable tools.
• Experience building dashboards and analytic interfaces using Dash, Streamlit, Panel, Tableau, or similar platforms.
• Ability to develop basic web interfaces using HTML, CSS, and JavaScript.
• Strong SQL skills and experience querying relational databases.
• Experience using Git-based version control platforms such as GitLab or GitHub.
• Familiarity with containerization technologies (e.g., Docker) and deploying containerized applications.
• Working knowledge of DevSecOps principles and secure software development practices.
• Proficiency with geospatial processing frameworks such as GDAL or ArcPy.
• Proficiency with GIS desktop software such as ArcGIS Pro or QGIS.
• Ability to write clear, concise technical documentation related to software systems and automated workflows.
• Ability to operate independently at a senior level with limited oversight.
• Familiarity with Activity Based Intelligence (ABI), All-Source, or Multi-INT analysis environments.
• Familiarity with USSOCOM and broader U.S. military organizational structures.
• Familiarity with common Intelligence Community (IC) data repositories.

#LI-GM1

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

ENSCO, Inc. is seeking a Sr. Machine Learning Engineer with direct experience and applications with using Machine Learning (ML) and Deep Learning (DL) models, frameworks, architectures, pipelines, and advanced data analytics, to address difficult problem sets.  Work closely with other senior scientist to understand problem sets, physical data feature sets and parameters.  The successful candidate must have demonstrated understanding of signal processing, data fusion, feature extraction, and be able to apply it towards ML and DL solutions.  Assess algorithm performance of features by building datasets and designing and executing well-controlled experiments.
 
ENSCO's Mission Systems Group (MSG) provides innovative customized products and services vital to national safety and security.  A primary focus area is the development of advanced algorithm development and integration for multipurpose data sets.
 

Qualifications Required:
•         Bachelors degree in Machine Learning, Data Science, Mathematics, or equivalent in a related discipline.  Direct relevant military experience will also be considered.
•         Minimum of 5 years related industry experience in machine learning, data science, and analytics.
•         Proven track record of successful data science and algorithm implementation.
•         Provide mentorship to junior ML engineers.
•         A self-starter with excellent oral and written communication skills.
•         Experience navigating and programming within the Linux environment.
•         Experience working with structured and unstructured databases.
•         Advanced proficiency with data science languages (e.g. Python, Matlab,)
•         Demonstrated experience with Deep Learning frameworks (e.g. PyTorch, TensorFlow/Keras, scikit-learn, MXNet).
•         Experience working with large data sets and ability to extract relevant information from data sets.
•         An Active Secret clearance is required for this position, for which you must be a U.S. Citizen
 
 

Qualifications Desired:
•         Masters or PhD degree in Machine Learning, Data Science, or Mathematics, or equivalent.
•         Experience with ML/DL algorithms extracting signal from noise.
•         Past experience being able to develop solutions using disparate data sets through ML techniques.
•         DevOps experience involving CI/CD pipelines to build and deploy.
•         Experience working with container orchestration technologies (e.g. Docker/Kubernetes).
•         An Active TS/SCI clearance.
 

Work Location Type: Hybrid
Required Certifications: None
U.S. Citizenship Required: Yes
Security Clearance Required: Secret
Employment Type: Regular Full-time
Background Check Type:  7 Year Pre-Employment
Drug Screen Required: None
Position Contingent Upon Contract Award: Yes