Founding Applied Data Scientist (AI)

Location: New York City, on-site. The New York team works in person five days a week, with flexibility as needed.

Company

hirify.global develops an agentic AI platform that detects, monitors, and removes digital impersonation, fraud, AI-driven scams, and identity abuse.

What you will do

• Own analytical data pipelines and infrastructure across product, business, and AI performance data.
• Define the semantic layer, warehouse models, and canonical metrics for activation, usage, retention, customer value, operational efficiency, and agent effectiveness.
• Partner with Product and Finance on pricing models, usage-based packaging, margin analysis, and customer-level profitability.
• Work with Platform Engineering on AI performance metrics, evaluations, benchmarking, observability, and reliability reporting.
• Build dashboards, analyses, decision-support systems, data quality checks, documentation, and metric definitions.
• Hire and onboard the Data Team and establish the long-term roadmap for data infrastructure, analytics, and applied data science.

Requirements

• 5+ years of combined experience as an Engineer, Analytics Engineer, Data Scientist, or in a closely related role.
• Strong SQL proficiency, ideally with production experience in Postgres and modern analytical modeling patterns.
• Experience building reliable data pipelines, data models, semantic layers, or internal analytics infrastructure.
• Experience defining product and business metrics from first principles and working with AI evaluation or model performance measurement systems.
• Strong product judgment, analytical communication skills, and the ability to work with Product, Engineering, Finance, and GTM.
• High ownership and comfort building foundational systems in an early-stage, fast-moving environment.

Nice to have

• Experience with Hex, Langfuse, Braintrust, Arize, Phoenix, OpenTelemetry, ClickHouse, BigQuery, Snowflake, Databricks, DuckDB, or dbt.
• Experience with usage-based pricing, unit economics, experimentation, causal inference, forecasting, or decision science.
• Experience evaluating AI agents, LLM products, fraud systems, abuse detection, cybersecurity, or trust and safety products.
• Production-quality Python or TypeScript experience and prior startup or early data hire experience.

Culture & Benefits

• In-person collaboration from a waterfront Brooklyn office.
• 100% company-paid medical, dental, and vision coverage for employees.
• Flexible PTO.
• Annual company retreats and regular in-person events.
• Lean, high-ownership environment with a focus on clarity, autonomy, and velocity.