Fluency in Python
Experience with LLM lifecycle: prompt design/engineering, prompting techniques (RAG, few-shot, CoT, etc.), vector databases, multimodality, fine-tuning, and evaluation.
Proven data science experience: You’ve been a key contributor to impactful projects and know how to deliver results with real-life outcomes.
Statistical & causal ML fundamentals: expertise in experimental design, uncertainty quantification, and rigorous model evaluation across tabular, time-series, and foundation-model fine-tuning tasks.
Deep learning experience: Expertise in building/training NLP or computer vision models with PyTorch, TensorFlow, or JAX.
Agile & AI-powered development: You run lean Kanban/Scrum cycles and leverage AI-powered tools like Cursor to prototype quickly and ship high-impact solutions.
Growth mindset: You embrace challenges, value progress over perfection, and constantly seek to improve.
Self-management: You can work independently, take ownership of projects, and deliver without constant oversight.
Product and UX understanding: You care about delivering a seamless, user-friendly experience.
Effective communication in English: Clear, concise, and maybe even witty communication is essential.

Remote-first culture: Work from anywhere, or join us in one of our offices.
Flexible schedules: We care about outcomes, not micromanagement.
Competitive pay: Regular performance-based raises and a diversified employee equity program.
Opportunities for growth: Work on cutting-edge R&D and propose projects that could become our next skunkworks focus.
Supportive environment: A team that collaborates, mentors, and shares knowledge.
Perks: Health insurance, free lunches (at the office), weekly knowledge-sharing talks, and an annual team retreat.

Data Scientist

Key skills