Research Scientist

Outset

. Co-design and run studies comparing system-generated responses with human responses using qualitative and quantitative measures .

Posted 10/22/2026full-timeSan Francisco • California • United StatesMid-LevelSenior💰 $200,000 - $240,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in computational social science and statistical methodology, with a strong focus on designing and analyzing studies that benchmark simulation performance and improve model calibration. Proficient in data collection, analysis, and interpretation, with experience in peer-reviewed publication and presenting research findings.

Highest-signal resume keywords

PhD In Computational Social ScienceStatistical Methodology ExpertiseExperience Analyzing Large-Scale DatasetsFamiliarity With Machine Learning ApproachesExperience Designing Human Rating Studies

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Statistical AnalysisSurvey MethodologyExperiment DesignData CollectionModel CalibrationFine-Tuning Language ModelsBehavioral Data AnalysisInter-Rater Agreement MeasurementEmbedding-Based MethodsTelemetry Analysis

Soft Skills

CollaborationCommunicationCritical ThinkingResearch Presentation

Tools & Technologies

SQLSoftware LibrariesDatabasesAgentic Coding Tools

Industry Keywords

Computational Social ScienceHuman-Computer InteractionQualitative InterviewsEthnographic MethodsGenerative AgentsDigital TwinsSimulation of Human RespondentsComputational Linguistics

Tech Stack

Tools & technologies

SQL

About the role

Key responsibilities & impact

Co-design and run studies comparing system-generated responses with human responses using qualitative and quantitative measures
Design, justify, and refine performance measures
Apply and adapt statistical techniques from survey methodology and large-scale social data analysis to benchmark and improve simulation performance
Design evaluations and experiments with pre-specified analysis plans
Design and oversee human rating studies, including rater training, coding rubrics, and inter-rater agreement measurement
Design data collection from third-party data sources and human participants, including longitudinal and repeated-measures studies
Contribute to the research agenda for new modeling approaches, including evaluation of fine-tuned models and model calibration
Specify analyses precisely enough for engineers to implement
Co-author papers, preprints, and presentations
Work directly with and report to the Head Scientist
Choose research topics, design studies, define measurement approaches, interpret findings, and write results for internal decision-making and potential academic publication
Bring methodological training in computational social science, data science, survey methodology, human-computation interaction, and experiment design

Requirements

What you’ll need

A completed or nearly completed PhD in computational social science, communication, HCI, sociology, political science, psychology, statistics, or a related field
Peer-reviewed publications on which you were a primary author
Working command of graduate-level statistical methodology common to social science, including the assumptions behind each
Experience analyzing large-scale telemetry and behavioral datasets, with attention to the validity of the resulting inference
Familiarity with machine learning, spanning classical, nonparametric, and LLM-based approaches, including how transformer-based language models work, what fine-tuning does, and how the major model families differ
Fundamentals of computing: file systems, software libraries, databases, SQL, and tabular data
Ability to work in an environment where most code is produced through agentic coding tools, and to read and check that code
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, for example with 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 the startup ecosystem
Familiarity with qualitative interviews and ethnographic methods
Familiarity with topics in computational linguistics
Legally authorized to work in the United States
Willing to work 4 days a week onsite in the San Francisco office

Benefits

Comp & perks

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