Advise customers on research objectives, methodology, sampling, and study design, and manage research engagements from scoping and setup through data collection, quality assurance, analysis, and reporting. Lead client conversations and collaborate with Sales, Customer Success, Product, and Supply teams to deliver actionable insights and improve research processes.
Audit existing lifecycle journeys and tools, identify activation and retention gaps, and prioritize improvements with Growth Marketing, Product, and Customer Success. Build and launch email and in-app onboarding, retention, reactivation, and expansion programs; define PQL signals, run experiments, report results, and document processes.
You will be responsible for scaling and managing the lifecycle program, including onboarding, activation, retention, and reactivation strategies. Additionally, you will collaborate with cross-functional teams to define product-qualified signals and optimize the self-serve user journey.
You will design, build, and maintain scalable data models and semantic layers to ensure reliable data for BI and AI systems. Additionally, you will implement LLM-powered transformations and agentic workflows while ensuring data integrity and cross-functional collaboration.
You will scale and ship the foundations of the lifecycle program, including onboarding, activation, retention, and reactivation across email and in-app channels. Additionally, you will define product-qualified signals and collaborate with cross-functional teams to drive user behavior and product adoption.
You will lead the end-to-end recruitment lifecycle for the Product and Design teams, partnering with senior leadership to define and execute hiring strategies. Additionally, you will implement data-driven sourcing techniques to attract top-tier talent and foster a strong employer brand.
Lead and coach engineering teams to deliver high-quality software while nurturing the professional growth of individual engineers. Collaborate with product managers to define technical strategy, manage technical debt, and ensure the delivery of scalable, resilient systems.
The Senior Data Analyst will autonomously own analytics across the participant lifecycle, from acquisition to retention. They will define strategic metrics, build executive-facing dashboards, and collaborate with cross-functional teams to optimize marketplace dynamics.
You will lead the development and implementation of algorithmic systems to optimize marketplace dynamics, including study matching and participant experience. The role involves translating complex business problems into actionable hypotheses and production-ready technical solutions.
You will manage and optimize Kubernetes clusters in GKE using Terraform while designing automation strategies to empower developers. Additionally, you will serve as a technical point-of-contact for cloud infrastructure and ensure compliance with security standards.
You will be responsible for designing meaningful customer journeys by collaborating with engineers, product managers, and data scientists. You will also conduct user research, create prototypes, and advocate for design decisions to improve the overall product experience.
Manage the operational delivery of human data for strategic AI customers by coordinating participant supply, workflows, and project timelines. Collaborate with Product and Engineering teams to identify bottlenecks and implement scalable process improvements.
You will manage complex research customer projects while identifying structural gaps and growth opportunities in participant supply. The role involves collaborating cross-functionally to build scalable solutions and optimizing participant onboarding and activation processes.
You will build and maintain scalable data pipelines and infrastructure to support analytics, ML workloads, and product-facing applications. Additionally, you will design data services and APIs while ensuring high standards for data quality, security, and observability.
The Strategic Projects Lead will own the end-to-end delivery of complex AI client programs, translating requirements into actionable data solutions. They will act as the primary point of contact, coordinating across internal teams to ensure project success, quality, and profitability.
You will manage end-to-end operational processes for participant pools and collaborate with product teams to scale workflows. This involves monitoring engagement metrics, implementing verification processes, and ensuring high-quality data delivery for AI projects.
You will manage end-to-end operational processes for participant pools and collaborate with product teams to scale these workflows. This involves overseeing participant onboarding, quality management, and aligning operational priorities with strategic AI customer needs.
You will build the infrastructure to evaluate AI agents by capturing traces at scale alongside human expert work. You will also collaborate with engineering and AI research teams to develop approaches for training, benchmarking, and improving agentic AI technologies.
The Senior Product Engineer II will define technical direction, shape the architectural roadmap, and drive engineering excellence across the team. They will also act as a mentor to other engineers while facilitating cross-team collaboration and technical discovery.
You will own the end-to-end delivery of complex AI projects, acting as the primary point of contact for clients to translate their requirements into successful data programs. You will also collaborate across internal teams to coordinate resources, manage project metrics, and improve delivery processes.
You will work within a cross-functional team to plan, build, and support high-value software products using agile methodologies. You will also be responsible for maintaining production systems with a 'you build it, you run it' mindset, ensuring high observability and performance.
Design and build scalable quality frameworks and infrastructure for human data used in training advanced AI models. Act as a strategic partner to clients and AI labs to translate model needs into robust evaluation strategies and annotation schemas.
You will lead the design vision and strategy across three cross-functional teams while acting as a hands-on designer for a core participant domain. Additionally, you will line-manage a group of designers and collaborate with engineers, researchers, and data scientists to build internal and external participant tools.
The Participant Recruitment Partner will drive the identification, attraction, and engagement of qualified participants while collaborating with client-specific AI delivery teams. They will also maintain the quality and diversity of participant pools and optimize recruitment processes.
The Participant Recruitment Partner will identify, attract, and engage qualified participants while collaborating with delivery teams to meet client needs. They will also manage recruitment processes and ensure the quality and diversity of participant pools.
