Data Scientist (AI)

TL;DR

Data Scientist (AI): Building custom propensity models that directly address clients' challenges, working at the intersection of customer data and hirify.global's data assets. Focus on designing creative solutions and building end-to-end modeling pipelines that turn data into measurable value.

Location: On-site in San Francisco, CA

Salary: $180,000 - $230,000 a year + Equity

Company

hirify.global is a people intelligence and AI company that gives go-to-market teams actionable insights.

What you will do

• Build and deploy custom machine learning models through the full lifecycle, including data exploration, feature engineering, training, validation, deployment, and ongoing evaluation.
• Synthesize diverse datasets by blending first-party customer data with hirify.global's proprietary data assets to engineer novel features.
• Act as a key technical partner to Product and Customer Success teams, providing insights that shape modeling strategy and translate customer needs into scalable data science solutions.
• Develop creative modeling strategies to address unique customer challenges across a variety of industries.
• Communicate model performance, methodology, and business impact to both technical and non-technical stakeholders.

Requirements

• 5+ years of professional industry experience in a data science or machine learning role.
• Proven experience building and deploying production-level predictive models (e.g., classification, regression, clustering).
• Expert proficiency in Python and core data science libraries (e.g., pandas, scikit-learn, NumPy, XGBoost).
• Advanced proficiency in SQL for complex data manipulation, aggregation, and analysis.
• A strong product-oriented mindset, with a demonstrated ability to connect data science work to tangible business value and customer success.
• Experience with the full machine learning lifecycle, including scoping, feature engineering, validation, deployment, and monitoring.
• The ability to communicate technical ideas to a non-technical audience.

Nice to have

• Experience with containerization technologies like Docker.
• Experience building and orchestrating data pipelines using tools like Airflow.
• Experience working in marketing analytics, ad-tech, fintech, or for a nonprofit organization.
• A Master's degree or Ph.D. in a quantitative field such as Statistics, Computer Science, Economics, or Mathematics.

Culture & Benefits

• Comprehensive benefits package.