Data Scientist - AI Research (GenAI)

Location: Not specified

Company

hirify.global builds production-grade AI and decisioning technology for insurance and banking, including pricing, underwriting, claims, customer engagement, and retention use cases.

What you will do

• Lead targeted AI research projects from initial hypotheses through production-ready solutions.
• Research and build LLM, RAG, agentic, and other modern AI workflows for integration into the product ecosystem.
• Establish and improve evaluation frameworks for LLM accuracy, safety, and business alignment.
• Partner with software developers and product managers to integrate scalable machine-learning features.
• Track emerging AI research, test state-of-the-art methods, and accelerate research execution.

Requirements

• 3–5 years of industry experience as an AI Researcher or Data Scientist.
• M.Sc. in Data Science, Computer Science, Statistics, Mathematics, or a related quantitative field.
• Strong theoretical and practical knowledge of classical machine learning and advanced statistical modeling.
• Experience with RAG pipelines, agentic workflows, autonomous AI systems, and rigorous LLM evaluation.
• Experience with AI development tools such as Claude Code, Cursor, GitHub Copilot, and advanced prompting frameworks.
• Ability to communicate complex mathematical and technical concepts to both technical and non-technical stakeholders.

Nice to have

• Finance experience in areas such as risk modeling, algorithmic trading, fraud detection, or financial time-series forecasting.
• Knowledge of causal inference for measuring business impact beyond correlation.
• Experience designing and training deep neural networks with PyTorch or TensorFlow.

Culture & Benefits

• Autonomy to execute research initiatives and contribute to the product roadmap.
• Resources and support for working with current GenAI models and frameworks.
• Collaborative environment focused on technical excellence and product quality.
• Low-bureaucracy culture with close collaboration across research, engineering, and product.