Data Scientist, User Operations
As a Data Scientist on User Operations, responsibilities include building and owning metrics, classifiers, and data pipelines that determine automation eligibility, effectiveness, and guardrails; designing and evaluating experiments to quantify the impact of automation and AI systems on user outcomes like resolution quality and satisfaction; developing predictive and statistical models to improve how OpenAI's support systems automate, measure, and learn from user interactions; partnering with engineering and product teams to create feedback loops that continuously improve AI agents and knowledge systems; translating complex data into clear, actionable insights for leadership and cross-functional stakeholders; developing and socializing dashboards, applications, and other tools to enable self-serve product data queries; contributing to the establishment of data science standards and best practices in an AI-native operations environment; and partnering with other data scientists across the company to share knowledge and synthesize learnings.
Senior Data Scientist (AI)
As a Data Scientist (AI) on Heidi’s Model Team, the responsibilities include partnering closely with the AI Engineering team to strengthen the foundations of data pipelines, analytics, experimentation frameworks, and reporting systems. The role involves collaboration with engineers and product teams to design, implement, and analyze online A/B tests to measure product impact; designing dashboards, running analyses, and providing clear reporting to inform product and research decisions; gaining hands-on experience with large language models through applying fine-tuning techniques to improve performance in healthcare-specific tasks; supporting the engineering team in deploying models into production environments to ensure scalability, reliability, and integration with clinical workflows; exploring approaches for model personalization, domain adaptation, and context-aware inference to enhance clinician productivity and patient care; partnering with data, engineering, product, and medical knowledge teams to align data and model work with Heidi’s healthcare AI mission; and continuously staying updated with emerging AI and ML research to expand from data-focused tasks to advanced model science.
Head of Data Science and Machine Learning, Global Forecasting
Build and manage a team of applied data scientists and ML engineers to develop forecasting platforms at scale; design and own the roadmap for the forecasting platform in partnership with cross-functional stakeholders; collaborate closely with Strategic Finance teams to integrate forecasts into planning processes and executive decision-making; work with cross-functional partners to adopt automated forecasting solutions; own the entire modeling lifecycle including scoping, feature engineering, model development and prototyping, experimentation, deployment, monitoring, and explainability; research and evaluate emerging forecasting tools and techniques; translate technical outputs into business-aligned recommendations and decision frameworks.
Data Scientist
Own data and evaluation across multiple customer projects by designing metrics, running experiments, and building dashboards to track model and workflow performance. Evaluate and refine LLM-based systems by analyzing outputs, tuning prompts, and measuring accuracy and coverage across varied insurance workflows. Analyze and communicate insights from production data to improve accuracy, coverage, and reliability. Work closely with the CTO to define success metrics and productionize AI systems. Collaborate with customers to translate workflows into measurable outcomes. Work in-person from the San Francisco HQ on a 5-day week schedule.
Data Scientist, AI Video Agent (Vancouver)
The Data Scientist will build and scale Opus's data capabilities, working at the intersection of data engineering, applied data science, and product strategy. Responsibilities include designing, implementing, and maintaining robust data pipelines across multiple sources such as GCS, MongoDB, and SaaS platforms, ensuring scalable ingestion, transformation, and governance of structured and unstructured data. The role involves leading advanced analyses related to growth, CRM/CX, payment flows, web tracking, marketing attribution to measure ROI, user lifecycle and retention analysis, predictive modeling for personalization and recommendations, user segmentation and tagging, and evaluating CX metrics like NPS and CSAT to inform product and operational improvements. The Data Scientist will establish best practices in A/B testing and post-experiment evaluation, partner with product and business teams to design experiments and interpret results with rigor in experiment design and causal inference. They will define the data science roadmap aligned with company goals, mentor and grow a team of data engineers and analysts, and act as a thought partner for GTM and BD initiatives to enable data-driven decisions.
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