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Outset has invented AI-powered user interviews that enable global brands like HubSpot, Microsoft, Uber, and Nestle to conduct qualitative research at unprecedented speed and scale. The company is disrupting a $140B+ research industry by replacing slow, expensive incumbent services with AI-driven alternatives. Backed by top Silicon Valley investors (Radical Ventures, M12, Y Combinator, 8VC, Adverb Ventures), Outset raised $30M in Series B funding in December 2025 and achieved 8x business growth in the past year.
Outset's core technology builds digital twins—AI systems that represent specific real people and respond to research questions as those people would. The Digital Twins Team runs an ongoing research program to measure and improve how faithfully these systems reproduce human responses and behavior across different levels of analysis.
As Research Scientist, you will work directly with and report to the Head Scientist. Your responsibilities include:
- Co-design and execute studies comparing system-generated responses with human responses using qualitative and quantitative measures
- Design, justify, and refine performance metrics
- Apply state-of-the-art statistical techniques from survey methodology and large-scale social data analysis to benchmark and improve simulation performance
- Design experiments with pre-specified analysis plans
- Design and oversee human rating studies, including rater training, coding rubrics, and inter-rater agreement measurement
- Coordinate data collection from third-party sources and direct human participants, including longitudinal and repeated-measures studies
- Contribute to research agenda for new modeling approaches, including evaluation of fine-tuned models and model calibration
- Specify analyses with sufficient precision for engineering implementation
- Co-author papers, preprints, and presentations
You will bring methodological training in computational social science, data science, survey methodology, human-computer interaction, and experiment design. This is a high-impact role at a fast-growing Series B company where research directly informs product development and competitive advantage.
QUALIFICATIONS (Required):
- Completed or nearly completed PhD in computational social science, communication, HCI, sociology, political science, psychology, statistics, or related field
- Peer-reviewed publications as primary author
- Working command of graduate-level statistical methodology common to social science, including assumptions behind each technique
- Experience analyzing large-scale telemetry and behavioral datasets with attention to inference validity
- Familiarity with machine learning spanning classical, nonparametric, and LLM-based approaches; understanding of how transformer-based language models work, what fine-tuning does, and how major model families differ
- Fundamentals of computing: file systems, software libraries, databases, SQL, and tabular data
- Ability to work in environment where code is produced through agentic coding tools; ability to read and check that code
PREFERRED QUALIFICATIONS:
- Experience fine-tuning open-weight language models on survey, experimental, or behavioral data
- Experience building or evaluating calibrated confidence or error-prediction models, including deriving decision thresholds from human judgments
- Experience measuring similarity of open-ended text using embedding-based methods
- Experience designing or running panel-based data collection with human participants
- Experience presenting research at academic and/or industry conferences
- Prior work on generative agents, digital twins, or simulation of human respondents
- Familiarity with startup ecosystem
- Familiarity with qualitative interviews and ethnographic methods
- Familiarity with computational linguistics topics
