Fullstack Data Scientist (AI/NLP)

TL;DR

Fullstack Data Scientist (AI/NLP): Developing sophisticated algorithms and internal tools to analyze complex behaviors of advanced chatbots and agentic threads for millions of users with an accent on uncovering hidden performance gaps and opportunities for breakthrough improvements. Focus on translating theoretical AI/ML research into production-grade implementations and defining data-driven engineering objectives for conversational AI.

Location: Hybrid work model balancing office and remote work. The office is conveniently located next to the Prilly-Malley train station in Lausanne, Switzerland.

Company

hirify.global is a leader in digital employee experience management software, providing IT leaders with unprecedented insight to diagnose and fix issues impacting employees before they notice.

What you will do

• Develop sophisticated algorithms and internal tools to dissect chat logs and agent threads, uncovering performance gaps.
• Execute end-to-end data science projects, adopting an iterative, scientific approach to solve real-world challenges in agentic AI.
• Assess the true impact of implemented changes on user experience and system performance through rigorous, statistically sound evaluation.
• Define complex, open-ended problems clearly, translating high-level business goals into concrete, data-driven engineering objectives.
• Analyze massive datasets to decode the "why" behind AI behavior, identifying patterns others miss.
• Collaborate with product managers, engineers, and designers to co-create the future of the AI platform.

Requirements

• BSc/MSc in Computer Science, Data Science, Mathematics, or a related field.
• Strong critical thinking and problem-solving skills, with a relentless drive to deliver practical, high-impact results.
• Deep proficiency in Python and its data science ecosystem (pandas, scikit-learn, numpy, etc.).
• Solid understanding of standard machine learning algorithms and statistical methods, with the intuition to know which tool fits the problem.
• Experience delivering data science projects end-to-end, from raw data collection and exploration to building robust tools or deploying models.
• Ability to read academic literature and implement complex research concepts into working code.
• Strong communication skills, with the ability to explain complex data concepts to diverse stakeholders.
• Experience with modern data visualization tools (e.g., matplotlib, seaborn, plotly) or BI platforms.
• Fluent in English (spoken and written).

Nice to have

• Hands-on experience with LLMs and modern NLP techniques (Prompt Engineering, RAG, Chain-of-Thought).
• Experience working with advanced chatbots, conversational AI, or autonomous agentic systems.
• Familiarity with cloud-native environments (AWS) and containerization (Docker).
• Knowledge of MLOps best practices, ensuring reproducibility, automated evaluation, and seamless model lifecycle management.

Culture & Benefits

• Permanent contract and a competitive compensation package.
• Hybrid work model balancing office and remote work, with flexible hours and unlimited vacation (plus 25 days of holidays).
• Free access to a fitness centre inside the building and reimbursement of the half-fare travel card for public transport.
• Reimbursement up to 50% of the cost of French classes.
• Regular company and team events like Voluntary Days, Pizza talks, Team Building activities, and Meetups.
• Bonuses for referring successful hires after three months of continuous employment.
• A relocation package to people who are coming from another country.