Data Scientist

The Role

We're looking for Data Scientists who will help implement, evaluate, and improve LLM-based applications (agentic applications). You’ll join our team as one of our earliest hires. You will work directly with the founders (ex-Google, ex-Silver Lake) and own key technical decisions from day one.

Responsibilities

• Develop innovative ways to evaluate the performance of agentic AI systems, track them over time, and perform prompt/context optimization and adapter tuning where necessary/appropriate to improve the performance of LLM-based applications.
• Integrate cutting-edge models, proprietary data, and innovative architectures to transform business workflows into AI-native processes.
• Design, implement, and validate these systems through rigorous benchmarking and real-world deployment.
• Critically explore recent advancements drawing from the full breadth of related exploratory efforts to establish company-wide perspectives and opportunities for innovation.
• Drive the state of art forward through bold experimentation.
• Understand the work of an investment analyst and apply statistics, machine learning, and data science to streamline tasks like sourcing, screening, due diligence, and asset monitoring.

Requirements

• Experience Building with Models, not just Building Models: Develop intelligent systems using models rather than training or fine-tuning them. Expertise in compound AI systems, agentic collaboration, and associated techniques (ensembling, ReAct, graph-of-thoughts, etc.) is ideal.
• Uses AI Every Day: Before you can revolutionize someone else’s workflow, you need to revolutionize yours. Using tools like ChatGPT, Cursor, Notebook LM, and Claude Code to accelerate your workflow is expected.
• Strong Programming and Data Analysis Skills: Need strong programming skills to prove-out your ideas.
• Biases Towards Showing vs. Telling: Customers want to see the power of AI today, not discuss the most elegant idea that will take 5 years to realize. Great Data Scientists come from diverse backgrounds and are unified by deep curiosity, pragmatism, and engineering excellence.

Qualifications

• A deep understanding of how to design and evaluate LLM-based applications.
• Ability to interpret statistical insights to non-technical or executive audiences.

Skills

• Strong programming skills.

Benefits

• No specific benefits mentioned.

Pay

• No specific pay mentioned.

Schedule

• No specific schedule mentioned.