Insurance Product Manager
The Insurance Product Manager is responsible for owning the full lifecycle of AI extraction workflows on the platform, including scoping, architecture, prototyping, evaluation, and iteration. They will design and build complex insurance workflows such as submission intake, policy comparison, underwriting audits, and claims workflows into structured, testable AI workflows from scratch. The role includes defining ground truths and evaluation sets to measure accuracy and quality, running continuous benchmarks, and identifying quality gaps before customers do. They will work directly with customers and Forward Deployed Engineers to configure, test, and iterate workflows toward production, bringing insurance process expertise and technical judgment to every deployment. The Insurance Product Manager acts as the bridge between domain expertise and engineering teams by translating insurance needs into technical solutions.
Data Scientist, Integrity
In this role, you will design and build systems for fraud detection and remediation while balancing fraud loss, cost of implementation, and customer experience. You will work closely with finance, security, product, research, and trust & safety operations to holistically combat fraudulent and abusive actors on the system. Additionally, you will stay abreast of the latest techniques and tools to stay several steps ahead of determined and well-resourced adversaries, and utilize GPT-5 and future models to more effectively combat fraud and abuse.
Senior Data Scientist
As a Senior Data Scientist at Norm, you will join the growing data team to build and scale analytics capabilities. You will develop data models and insights that power the AI compliance engine and help measure, understand, and optimize the product. Responsibilities include designing and maintaining multi-dimensional measurement frameworks for evaluating AI performance across the Norm Law workflow, analyzing telemetry and behavioral logs to understand interactions with AI-generated work, designing and running experiments with rigorous statistical design and clear hypotheses, developing frameworks to measure and communicate performance across key dimensions of legal work quality, implementing product analytics to understand how enterprise clients engage with AI-driven compliance and legal workflows, building self-service analytics capabilities for legal engineers and business stakeholders, contributing to ELT processes using dbt, Airflow, and cloud data warehouses, and helping establish data governance practices that meet enterprise security and regulatory compliance requirements.
Data Scientist, Growth
The Data Scientist, Growth at Eight Sleep is responsible for leading complex forecasting challenges that impact supply chain, marketing spend, and business growth. This includes building advanced demand forecasting models to prevent stock-outs during peak periods and avoid overcommitting capital on inventory, developing marketing spend optimization algorithms that factor in seasonality, macro trends, and cross-channel effects, creating experimentation frameworks for incrementality testing across marketing channels like Meta, Google, and YouTube with statistical rigor, and designing marketing attribution models to handle complex customer journeys and multi-touch attribution challenges.
Senior Forward Deployed Engineer
Lead complex AI-driven deployments in production, owning technical delivery across multiple deployments from scoping high-impact Agentic AI use cases to stable production. Apply technical expertise and problem-solving skills to design solution architectures, develop decision logic, deploy production-grade Generative AI agents, and align with key customer stakeholders, ensuring an outstanding experience and rapid time to value. Scope work effectively, sequence delivery, proactively remove blockers, and make trade-offs between scope, speed, and quality for successful and timely project delivery. Partner with product management to convert customer needs into actionable insights that influence the product roadmap. Develop reusable resources, best practices, and tools to scale the forward deployed engineering function across the organization.
Lead Forward Deployed Engineer
As a Lead Forward Deployed Engineer, you lead complex AI-driven deployments in production, owning technical delivery across multiple deployments from scoping AI use cases to stable production. You apply technical expertise, problem-solving skills, and creativity to help organizations address challenges by designing solution architectures, developing decision logic, deploying production-grade Generative AI agents, and aligning with customer stakeholders while ensuring rapid value for customers. You scope work, sequence delivery, remove blockers, and make trade-offs between scope, speed, and quality to ensure project success. You partner with product management to translate customer needs into product insights influencing the product roadmap. You develop reusable resources, best practices, and tools to scale the engineering function and actively coach and mentor junior engineers.
Software Data Engineer
Collaborate with Machine Learning, Full-stack engineers and Science to solve complex document mining challenges, capture and model additional scientific experiments, scale data pipelines for rapid and reliable data transfer from research to platform, work with semi-structured and unstructured data, define and apply best practices for technologies in a cloud-based environment, architect and maintain robust data pipelines that ingest diverse sources and use large language models (LLMs) for high-fidelity entity extraction into structured formats, implement evaluation frameworks to monitor extraction models' accuracy, drift, and hallucination rates in production pipelines, lead or consult on engineering design proposals according to the Platform Stream roadmap, make independent technical decisions based on business context and team goals, proactively identify new opportunities and implement project improvements, respond with urgency to operational issues and own resolution within one's responsibility, and challenge the status quo by proposing new technologies or ways of working.
Data Scientist, Preparedness
The Data Scientist on the Preparedness team is responsible for evaluating and improving mitigation systems including classifiers and detection pipelines across various domains such as biosecurity, cybersecurity, and emerging risk areas. They diagnose false positives and false negatives through deep error analysis, root cause investigation, and make clear recommendations for mitigation adjustments. They build monitoring and measurement frameworks to track the effectiveness of mitigations over time and across user segments and use cases. This role involves identifying trends in over-blocking versus under-blocking, quantifying customer impact, and proposing prioritized interventions. The Data Scientist develops insights from customer feedback, complaints, and usage patterns to detect shifts in adversarial behavior and system failure modes. They expand risk monitoring into new areas including cybersecurity threats and scenarios involving model loss-of-control or sabotage in partnership with domain experts. Finally, they communicate results to technical and executive stakeholders using concise narratives, decision-ready metrics, and clear tradeoffs.
Senior Data Scientist - Data Foundations & AI
As a Senior Data Scientist on the Data Foundation & AI team at Plaid, you will define and operationalize quality measurement across enrichment and AI systems to ensure products deliver reliable, high-impact outcomes for customers. Responsibilities include owning and evolving evaluation frameworks, investigating customer-facing quality issues, building scalable evaluation systems, measuring AI system effectiveness in a principled way, automating workflows using modern AI tools, and influencing roadmap decisions through data. You will partner closely with product and engineering teams, use data-driven insights to inform decision-making, and raise the quality bar across AI-powered experiences.
Senior Software Engineer
Own full lifecycle management of advertising systems, from experimentation through deployment and continuous enhancement. Design, implement, and deploy data-driven algorithms and computational models for intelligent advertising platforms. Build scalable, high-performance software components that enable content personalization for publishers and brands. Monitor and evaluate performance of deployed models to ensure high system reliability. Analyze performance data and implement improvements to optimize accuracy and efficiency. Conduct ongoing research into emerging algorithms and data processing techniques, aligning solutions with latest academic and industry advancements. Proactively integrate new methodologies and technologies to strengthen and expand system capabilities. Perform data wrangling and preprocessing using SQL and related tools to prepare structured training data. Ensure data integrity and usability through best practices in validation, error handling, and resource management.
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