Staff Data Scientist

15Five is the AI-powered performance management platform built for business impact. 15Five’s AI-powered all-in-one people management system is easy to use,
delivers effortless insights, and enables managers to lead with impact so that companies and their people can thrive. Within the flow of work, HR leaders are empowered with data-driven insights and recommendations while managers are transformed into change-makers, accelerating engagement, performance, and retention. 15Five combines generative AI, custom analytics, and human-centered principles within a complete platform, including 360° performance reviews, engagement surveys, goal tracking, manager coaching and training, and ongoing feedback tools like guided 1-on-1s and check-ins.     A career at 15Five is the chance to have high impact in a fast paced, remote startup environment that operates with focus, urgency, and accountability. Every role and every hire meaningfully impacts our trajectory.   We’re a high-performance, high-purpose team that gives you the chance to Build the Future of Work. We run on High Standards and High Support — holding a high bar for results, ownership, clarity, and disciplined execution, while investing in manager enablement, skill development, and whole-person care. We are committed to a No B.S. environment, meaning we anchor ourselves in truth, course-correct in real time, and expect people to lean into direct conversations. We are focused on ensuring every 15Fiver can Work in the Future and that starts with proactively using AI across all aspects of your role to increase leverage, speed, and impact.   If you're energized by a fast pace, high standards, and high accountability for yourself and others, you'll thrive here and we encourage you to apply.
We take pride in our position as an innovator in the Human Resources landscape. This wouldn’t be possible without our outstanding team of engineers that apply next-generation thinking to our software - their abilities allow us to continually elevate the user experience and push leading performance-management technology into the global market.   As an experienced Staff Data Scientist, you will play a critical role driving the discovery, creation, and integration of AL/ML models into our performance-management platform at 15Five. You will combine statistical methods with engineering best practices to help meet our business needs. We will rely on your statistical analysis skills, as well as insight for collecting, filtering, and preparing meaningful training data for AI/ML projects. You will be instrumental in modeling HR data and building rich structured context to power our knowledge base as well as AI agents engaging with our customers. You will work closely and collaborate with software and data engineers and guide them on operationalizing your work. You will be a self-starter, and build from the ground up leveraging your experience.

AREAS OF FOCUS

• Applied data science
• Statistical analysis
• Feature engineering
• Supervised/Unsupervised model training & delivery

RESPONSIBILITIES

• Data analysis and exploration: Conduct in-depth analysis of large structured and unstructured datasets to uncover patterns, insights, and signals that inform AI models, knowledge representations, and product decisions.
• Statistical modeling: Develop and apply statistical methods to identify patterns, trends, and correlations in HR performance, engagement, and behavioral data, supporting evidence-based insights and model development.
• Feature engineering and knowledge modeling: Design and engineer features from diverse data sources (e.g., reviews, surveys, behavioral signals, organizational data) to power machine learning models and construct structured AI context layers and knowledge representations used by intelligent systems and agents.
• Training data development: Lead the creation and curation of high-quality labeled datasets, including annotation frameworks, evaluation datasets, and ground truth benchmarks that support model training and validation.
• Machine learning model development: Design, develop, and train machine learning models (supervised, unsupervised, and representation-learning approaches) for use cases that enhance customer outcomes and enable intelligent product capabilities.
• Context layer and AI system support: Develop data structures, embeddings, and context-enrichment pipelines that enable AI agents to retrieve relevant organizational knowledge, behavioral insights, and product context.
• Model deployment and integration: Partner with engineering teams to operationalize models in