Lead or contribute to the design and execution of rigorous quantitative research and evaluation projects across multiple Education Systems and Policy initiatives.
Locations (6)
Arlington, Virginia, United States
Chapel Hill, North Carolina, United States
Chicago, Illinois, United States
Sacramento, California, United States
Austin, Texas, United States
United States
Compensation
$114,000—$140,000 USD
Responsibilities
Lead or contribute to the design and execution of rigorous quantitative research and evaluation projects across multiple Education Systems and Policy initiatives.
Apply appropriate quantitative methods to collect, manage, analyze, and interpret data, including leading inferential analyses for both causal and non‑causal research questions.
Develop, maintain, and document reproducible and collaborative analytic workflows, including data management processes and quality control procedures.
Review, quality‑check, and strengthen analytic code and outputs produced by junior staff; provide guidance and mentorship to promote best practices in analysis and documentation.
Translate complex analytic findings into clear, actionable insights for client reports, technical memos, presentations, and briefings.
Requirements
Master's or doctoral degree in statistics, mathematics, computer science, computational social science, education data science, or a related discipline.
Conduct data analysis, manuscript preparation, and laboratory work for SERDP, NSF, and NIH funded projects on protein-based sorbents and PFAS-receptor interactions.
Responsibilities
Analyze data and prepare manuscripts for SERDP, NSF, and NIH funded projects
Perform protein production, stability assays, and protein purification workflows
Conduct molecular docking and machine learning modeling
Mentor and train new students in the Ng group
Requirements
PhD in Environmental Engineering or a related field
Provide data analytics and statistics support on Internal Audit and process improvement projects, using tools such as Microsoft Fabric, SQL, Python, and various statistical packages.
Responsibilities
Provide data analytics and statistics support on Internal Audit and process improvement projects
Use data or statistical analysis tools for anomaly detection, process analysis, and policy decision-making
Design, develop, and maintain end-to-end analytics workflows in Microsoft Fabric
Help develop and implement continuous monitoring / auditing software solutions
Take part in investigative activities and translate them into actionable business intelligence
Requirements
MA/MS in a quantitative field (Mathematics, Statistics, Economics) or technical field (Computer Science)
Enrolled in a graduate degree program with exposure to data analytics and statistics coursework
Nice to have: 1 year of quantitative industry experience
Nice to have: Experience working with Business Intelligence tools
Develop and launch on-device machine learning technologies to keep users safe from fraud while maintaining privacy, designing models that work within resource constraints like model size and inference budgets.
Locations (2)
Austin, Texas, United States
New York City, New York, United States
Responsibilities
Develop and launch on-device technologies that keep users safe
Work closely with engineering, security, program management, and business partners
Build models that run in real time and in the background on the device
A senior hands-on applied science and engineering role focused on shaping the next generation of deep learning systems for personalization, including recommendation, ranking, retrieval, traveler understanding, sequential modeling, and foundation-model-based personalization.
Locations (2)
San Jose, California, United States
Seattle, Washington, United States
Compensation
The total cash range for this position in San Jose is $187,000.00 to $261,500.00. Employees in this role have the potential to increase their pay up to $299,000.00, which is the top of the range, based on ongoing, demonstrated and sustained sustained performance. The total cash range for this position in Seattle is $173,000.00 to $242,500.00. Employees in this role have the potential to increase their pay up to $277,000.00, which is the top of the range, based on ongoing, demonstrated and sustained performance.
Responsibilities
Design, develop, and apply machine learning solutions to real-world personalization, product, and business problems
Drive end-to-end scientific work across problem formulation, data exploration, feature engineering, model development, evaluation, and iteration
Partner closely with engineers, product, and business stakeholders to integrate machine learning solutions into services and workflows
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