Data Scientist (AI)

TL;DR

Data Scientist (AI): Expanding hirify.global’s ability to answer high-impact GTM and operational questions with speed, rigor, and trust with an accent on turning data into trusted insights. Focus on designing experiments and defining success metrics, and building and evaluating functional models that support decision-making.

Location: Remote

Company

hirify.global is the software supply chain security company.

What you will do

• Explore and analyze GTM and operational data to answer high-impact questions.
• Design experiments and define success metrics.
• Build and evaluate functional models that support decision-making.
• Partner with RevOps and AI Ops to scope problems and define metrics and success criteria.
• Ship clear, well-documented analytical artifacts for integration and building.

Requirements

• 3+ years of experience in applied data science, machine learning, analytics, or AI research
• Strong Python and SQL skills.
• Comfort with common DS/ML tooling (e.g., pandas, scikit-learn)
• Experience pulling/transforming data from real production systems, and turning large, messy data into insights and features.
• Exposure to model evaluation practices (baseline building, offline metrics, error analysis, experiment design)
• Ability to communicate insights clearly to non-technical stakeholders.

Nice to have

• Experience using platforms like Databricks, MLflow, or model serving/monitoring tools (at any scale)
• Familiarity with version control (Git) and collaborative workflows.
• Experience with LLMs/embeddings/RAG and how to evaluate them beyond “vibes”
• Any exposure to Sales, GTM, customer success tooling.
• Comfort building lightweight internal tools (small APIs, pipelines, automations) that help others move faster.

Culture & Benefits

• Company Wellness days - Company operations are shut down during some days of the year to enable all employees to pursue personal growth and enjoy additional rest.
• Paid Volunteer Time Off (VTO)
• Parental leave, diversity and inclusion working groups, and flexible working practices to allow employees to show up as their whole selves.