Staff Data Scientist

Role Description

We are seeking a Staff Data Scientist who is deeply curious about our product, our customers, and the employee relations data that sits at the heart of what we do. Reporting to the Director of Platform and Data Engineering, you will own the development of an authoritative, end-to-end understanding of our data:

• What it represents
• How it’s structured
• Where it’s reliable
• What it can tell us about workplace issues at scale

From that foundation, you’ll build the analytical models and customer-facing data products that help organizations understand patterns in their employee relations (ER) programs and benchmark against industry peers. This is a high-impact role where genuine product curiosity isn’t a nice-to-have; it’s the prerequisite for doing the work well. You'll bring rigorous statistical thinking and strong engineering fundamentals to everything from building the models that power our product to presenting benchmark findings directly to customers.

Qualifications

• Genuinely curious about products and the problems they solve
• Strong statistical foundations and practical engineering skills
• Comfortable diving into ambiguous data questions and building production-grade models
• Ability to explain reasoning clearly
• Bachelor's or Master's degree in Statistics, Data Science, Computer Science, or a related quantitative field — or equivalent practical experience
• 6+ years of experience in data science, applied statistics, or machine learning
• Proven track record building and deploying predictive models in production environments
• Strong Python skills across the data science ecosystem (pandas, scikit-learn, statsmodels, scipy, etc.)
• Solid SQL command with experience working with relational databases at scale
• Experience with Snowflake and cloud-based ELT patterns
• Azure experience preferred, particularly for model pipelines and container-based workloads (e.g., Kubernetes)
• Demonstrated experience with unstructured text data, including NER, PII detection and anonymization pipelines
• Experience evaluating LLM-powered features in production
• Proficiency in experiment design and A/B testing methodology
• Experience working with sensitive or compliance-adjacent data (HR, healthcare, legal, or financial) is strongly preferred
• Demonstrated ability to translate complex statistical concepts into clear, actionable narratives

Requirements

• Develop and continuously deepen a comprehensive understanding of HR Acuity's full data landscape
• Assess what makes HR Acuity's dataset competitively distinctive
• Build rigorous documentation, lineage, and data quality baselines for HR Acuity's ER dataset
• Design and build statistical models and machine learning solutions
• Apply NLP and text analytics techniques to extract structure, patterns, and signals from unstructured case data
• Own and elevate HR Acuity’s customer-facing analytics and benchmarking capabilities
• Design and execute experiments to measure the impact of product and analytical changes
• Collaborate with Data Engineering to ensure pipelines, schemas, and data models support analytical needs
• Partner closely with Product and Engineering to define metrics and evaluate feature performance
• Apply responsible data practices throughout all work
• Define and maintain the statistical evaluation framework for AI and ML features
• Establish data science standards, documentation practices, and reproducibility norms

Benefits

• Comprehensive medical, dental, and vision plans
• FSA or HSA options to suit your needs
• 401K plan that matches your contributions
• Paid leave for various life events, such as sickness, disability, or parenthood
• #Allin Shares Program
• Company paid holidays, birthday day off, closed 4th of July week and December holiday week, and 8 hours of volunteer time
• Half day summer Fridays and half day first Fridays
• Unlimited PTO policy
• Access to professional and personal support through our employee assistance program
• Remote work environment that fosters collaboration and creativity
• Competitive salary and meaningful opportunities for growth