Data Scientist

• Apply quantitative analysis, data mining, and statistical modeling to deliver actionable data insights
• Drive timely decision-making to improve and optimize product creation, execution, and adoption
• Collaborate with product managers, engineers, product marketers, and designers
• Use AI tools to develop scalable data solutions while maintaining accuracy and statistical integrity
• Identify key product trends and new product opportunities through data modeling
• Analyze product performance using core metrics
• Communicate insights through visuals, dashboards, and reports

Data Scientist – Level 3

• Apply quantitative analysis, data mining, and statistical modeling to deliver impactful, objective, and actionable data insights
• Drive informed and timely decision-making to improve and optimize how products are created, executed, and adopted
• Collaborate with product managers, engineers, product marketers, and designers
• Use AI tools to develop scalable data solutions efficiently while maintaining accuracy and statistical integrity
• Identify key product trends and new product opportunities through data modeling
• Design, implement, and track core metrics to analyze product performance
• Create visuals, dashboards, and reports to communicate insights effectively
• Initiate and drive projects to completion with minimal guidance

• Design and implement experiments and processes for evaluating business performance, new products, and product features
• Conduct analyses involving project design, data collection, analysis, summarizing findings, and presenting results understandably
• Compile appropriate data, apply multidimensional data aggregation, and perform profile analysis to evaluate business impact
• Handle large volumes of transaction-level data to derive actionable results efficiently
• Interact with stakeholders to understand business questions, craft methodologies to mine and analyze datasets, and deliver recommendations
• Keep up to date with the latest technology trends
• Mine, model, and analyze large datasets using predictive modeling techniques
• Build and validate statistical models, provide analytic support, and develop new criteria and/or strategies
• Produce regular reporting content for key stakeholder meetings, respond to ad hoc analysis requests, and generate insightful deep dives
• Support the Sales and B2B Marketing departments within a consumer finance company

Data Scientist III

• Build derived data products from Muon's infrared imaging missions across Muon's IR programs
• Implement and improve scalable algorithms for processing, transforming, and analyzing multispectral infrared imagery into derived geospatial products
• Contribute to derived product design and roadmap under senior scientists and product owners
• Contribute to technical and customer-facing design documents
• Support engagement with customer technical stakeholders, including Technical Interchange Meetings, customer questions, and program meetings
• Write production-ready code integrated into customer-facing data product pipelines and operational services
• Contribute to scientific quality, quantitative validation, and integrity of derived products
• Collaborate with software engineers, calibration scientists, and instrument engineers to design, build, and maintain operational data product services
• Learn topics including sensor geometry, georeferencing, wildfire and environmental monitoring, and cloud-native geospatial data engineering

Remote Sensing Data Scientist

• Design, build, and operate production-grade calibration and image-processing pipelines for multispectral infrared imagery from FireSat and SBEM missions
• Translate calibration algorithms into hardened, well-tested production code
• Own unit, integration, and regression testing across representative lab and on-orbit datasets
• Analyze pre-launch and on-orbit calibration data to derive, validate, and trend calibration coefficients
• Build monitoring, alerting, and automated diagnostic visualizations for calibration accuracy, noise, uniformity, and image-quality metrics
• Contribute to CI/CD, deployment, containerization, and observability tooling
• Partner with calibration scientists and the IR Instrument team on pre-launch and on-orbit calibration campaigns
• Drive code review, version control, documentation, calibration coefficient and lookup-table management, test coverage, and reliability improvements
• Work cross-functionally to ensure scientific quality, quantitative validation, and radiometric integrity of IR data products
• Learn measurement techniques, geospatial data engineering, software engineering, and customer-domain implications as needed

Senior Remote Sensing Data Scientist, Cal/Val

• Design, develop, and maintain scalable data pipelines and ETL/ELT workflows for foreign assistance data processing
• Build and optimize data models, schemas, and cloud-based data architectures for reporting, dashboards, and advanced analytics
• Implement data quality, validation, and monitoring processes
• Use automation and AI tools to improve efficiency and productivity
• Explore and analyze foreign assistance data upon request
• Support predictive analytics or light machine-learning workflows where appropriate
• Maintain documentation, metadata, and data governance standards aligned with Department of State policies
• Communicate technical issues to technical and non-technical audiences
• Take on adjacent responsibilities in a small, fast-moving team to ensure project goals are met
• Engage in continuous learning about new data technologies and their applications for Department of State clients
• Model behaviors supporting a non-hostile work environment free of discrimination, bias, unfairness, exclusion, offensive behaviors, and harassment

• Translate complex, high-ambiguity business challenges into multi-quarter data science roadmaps
• Drive methodology, design, and standards for the centralized experimentation framework
• Serve as the primary authority on causal inference, A/B testing, and hypothesis validation
• Architect and oversee production-grade statistical and machine learning models for bid/UA optimization, dynamic audience segmentation, user lifetime value, and multi-touch attribution
• Direct time-series forecasting and real-time event processing strategies
• Partner with ML Infrastructure and Data Engineering leads on model deployment, monitoring, and integration
• Mentor senior and mid-level data scientists
• Establish code and methodology standards and foster an evidence-based culture
• Translate technical findings into strategic narratives for executive stakeholders
• Influence product strategy and commercial investments

Lead Data Scientist

• Extract, prepare, and model large, complex data sets to develop advanced analytics and machine learning solutions
• Identify and evaluate new technologies to enhance data integration and quantitative analytics capabilities
• Own implementation and standardization of advanced analytics and modeling toolkits for data science teams
• Collaborate with data engineering on data management strategies, architecture, governance, and infrastructure
• Provide senior-level guidance on data science methodologies and approaches to technical teams
• Communicate insights and technical information to business leaders through verbal, written, and visual means
• Perform other duties and projects as assigned by business management

Principal Data Scientist

• Engage with business partners and stakeholders to understand their challenges and opportunities
• Explore large datasets using modeling, analysis, and visualization techniques
• Transform analytical results into insights and recommendations
• Contribute to the end-to-end development of predictive and prescriptive models for marketing, sales, finance, supply chain, and other business applications
• Design, build, and optimize workflows to streamline and automate data processing and delivery
• Develop and maintain applications that provide insightful capabilities through interactive and intuitive interfaces
• Apply statistics, data science, and machine learning to structured and unstructured data
• Create predictive models focused on NLP and GenAI

Data Science Co-Op, NLP, GenAI

• Recruit, hire, and develop a team of strategists and analysts
• Set strategic direction, standards, and delivery methodology for the portfolio strategy, analytics, insights, and consulting practice
• Manage performance, career development, and capacity planning across a distributed team
• Build repeatable frameworks, tools, and playbooks to scale delivery quality
• Identify portfolio rationalization, consolidation, expansion, and geographic repositioning opportunities
• Oversee portfolio assessments covering location strategy, space utilization, lease expirations, occupancy costs, and operational efficiency
• Own analytics from data infrastructure and modeling through executive-ready outputs
• Direct complex portfolio data analysis and benchmarking against industry standards
• Lead market insights, benchmarking, strategic planning workshops, and executive presentations
• Advise clients on high-priority portfolio decisions and translate real estate concepts for C-suite stakeholders
• Represent JLL's portfolio strategy and analytics capabilities in pitches, RFPs, and capability presentations
• Develop case studies and thought leadership content
• Coordinate with JLL Technologies on digital solutions and data platforms
• Contribute to research publications, white papers, and service innovation

Data Scientist jobs in United States

Data Scientist – Level 3

Data Scientist – Level 3

Data Scientist III

Remote Sensing Data Scientist

Senior Remote Sensing Data Scientist, Cal/Val

Data Scientist

Lead Data Scientist

Principal Data Scientist

Data Science Co-Op, NLP, GenAI

Portfolio Strategy & Analytics Leader, Portfolio Advisory