[Hiring] Staff Data Scientist @15Five

Role Description

As an experienced Staff Data Scientist, you will play a critical role driving the discovery, creation, and integration of AI/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

• 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.
• 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.
• 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.
• 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.
• 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.
• Develop data structures, embeddings, and context-enrichment pipelines that enable AI agents to retrieve relevant organizational knowledge, behavioral insights, and product context.
• Partner with engineering teams to operationalize models in production environments, ensuring scalability, reliability, and alignment with product architecture.
• Design evaluation frameworks and continuously monitor model performance, iterating on models, data pipelines, and features based on experimentation, feedback, and evolving business needs.
• Work closely with product, engineering, and design teams to translate business problems into data science solutions and ensure models deliver measurable value.
• Maintain clear documentation for datasets, modeling approaches, evaluation frameworks, and data pipelines to ensure reproducibility, transparency, and knowledge transfer across teams.
• Design evaluation datasets and benchmarking frameworks to measure AI agent performance, including retrieval quality, reasoning accuracy, and contextual relevance.
• Ensure that data used in models and AI systems meets privacy, security, and ethical standards, particularly when working with sensitive employee performance and engagement data.

Qualifications

• BS or higher in Computer Science, Statistics, Mathematics, Physics, or a related quantitative field, or equivalent practical experience.
• 7+ years of experience in data science, machine learning, or applied statistics in a production environment.
• Strong foundation in statistical methods and the ability to apply them to large, complex datasets to identify patterns, trends, and actionable insights.
• Demonstrated experience developing, evaluating, and deploying machine learning models that drive measurable business impact. Experience with large language models (LLMs), embeddings, or AI-driven systems is a strong plus.
• Strong programming skills in Python and SQL, with experience building data processing pipelines, training models, and analyzing large datasets.
• Experience working with modern data platforms including data warehouses, relational databases, and distributed data processing systems.
• Familiarity with MLOps practices and tools for model training, versioning, deployment, monitoring, and lifecycle management.
• Understanding of modern software development workflows, including version control (Git), CI/CD pipelines, code review, testing practices, and agile development methodologies.
• Strong ability to communicate complex technical concepts to non-technical stakeholders and collaborate effectively with product, engineering, and cross-functional teams.

Requirements

• $132,500 - $170,500 a year Annual Base Pay Range, US Full-Time Staff Data Scientist.
• Range may vary based on candidate's home location and proximity to different US compensation zones.
• This role's Total Rewards package includes participation in an annual discretionary company bonus program, equity awards, and comprehensive benefit and wellbeing offerings.

Benefits

• Medical, dental, vision with 15Five cost subsidy
• Employer paid Short-Term, Long-Term Disability, and Term Life
• Family planning support with enhanced medical plans and consultation programs
• Inclusive Benefits Stipend
• Access to mental health and wellness resources
• Flexible Time Off Program
• Generous paid leave for new parents
• Military leave
• Paid Company Holidays
• Sabbatical Program
• 401K with 4% Matching after 6 months
• Remote work
• Work with experts in leadership, culture, and personal development