Data Scientist (AI)

Location: Budapest, Hungary; hybrid work

Company

hirify.global is an enterprise agentic marketing platform built on a structured data platform for local businesses, connecting data to APIs, MCP servers, and generative interfaces. Its customers include brands and digital marketing partners in financial services, healthcare, retail, hospitality, and food.

What you will do

• Analyze hirify.global data sources to identify product and business opportunities.
• Design data models and metrics for customer-facing features and decision-making.
• Lead data science and ML research from problem framing and prototyping through engineering handoff.
• Develop and evaluate statistical, ML, and GenAI/LLM solutions across structured and unstructured data.
• Build reproducible prototypes and validate model quality, coverage, and business impact before production deployment.
• Partner with Product, Engineering, and business stakeholders to deliver production solutions, improve data pipelines and data quality, communicate trade-offs, and mentor teammates.

Requirements

• 3+ years of experience in data science, machine learning, or data analytics.
• Proficiency in Python and SQL for data analysis, modeling, and experimentation.
• Understanding of statistics, supervised and unsupervised learning, and model validation techniques.
• Experience with data modeling, data warehousing, and preparing datasets for analytical and product use.
• Familiarity with generative AI/LLM applications, including RAG, prompt engineering, agentic workflows, and evaluation.
• AI-first approach using AI coding assistants such as Codex or Claude while maintaining quality and security.
• Hands-on experience with AWS, GCP, or Azure.
• Strong problem-solving skills, independence in ambiguous situations, communication, and cross-functional collaboration.
• Bachelor’s or Master’s degree in Computer Science, Engineering, Math, or equivalent practical experience.

Culture & Benefits

• AI-first organization using modern AI and agentic workflows.
• Collaborative work with Product, Engineering, and business stakeholders.
• Commitment to responsible AI adoption, continuous learning, and mentoring.
• Equal opportunity employer providing reasonable accommodations as required by applicable law.