Job description

The Role We're looking for Data Scientists who will help implement, evaluate, and improve LLM-based applications (agentic applications). You will work directly with the founders (ex-Google, ex-Silver Lake) and own key technical decisions from day one. You’ll work on: ● Evals and Optimization You 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. ● Applied Research 0→1 System Design You integrate cutting-edge models, proprietary data, and innovative architectures to transform business workflows into AI-native processes. They design, implement, and validate these systems through rigorous benchmarking and real-world deployment. ● Exploratory Research – Bold, Big Bets You critically explore recent advancements drawing from the full breadth of related exploratory efforts to establish company-wide perspectives and opportunities for innovation. You act on these opportunities through bold experimentation, and drive the state of art forward. ● Data-driven investment decisions You understand the work of an investment analyst and can find ways to apply statistics, machine learning, and data science to streamline tasks like sourcing, screening, due diligence, and asset monitoring. Experience Required: ● Experience Building with Models, not just Building Models We develop intelligent systems using models rather than training or fine-tuning them. Ideal candidates have expertise in compound AI systems, agentic collaboration, and associated techniques (ensembling, ReAct, graph-of-thoughts, etc.). ● Uses AI Every Day Before you can revolutionize someone else’s workflow, you need to revolutionize yours. You should be using tools like ChatGPT, Cursor, Notebook LM, and Claude Code to accelerate your workflow. ● Strong Programming and Data Analysis Skills You need to have strong programming skills to be able to prove-out your ideas. ● Biases Towards Showing vs. Telling Our customers want to see the power of AI today vs discuss the most elegant idea that will take 5 years to realize. We believe great Data Scientists come from diverse backgrounds and are unified by deep curiosity, pragmatism, and engineering excellence. You Have: ● 8+ years experience ● A deep understanding of how to design and evaluate LLM-based applications ● Ability to interpret statistical insights to non-technical or executive audiences ● Strong programming skills Bonus: ● Experience in financial systems, risk modeling, or decision automation ● Familiarity with ML training and deployment ● Experience with embedded analytics

Requirements

Must-haves

Evals and Optimization
Applied Research 0→1 System Design
Exploratory Research – Bold, Big Bets
Data-driven investment decisions
You understand the work of an investment analyst and can find ways to apply statistics, machine learning, and data science to streamline tasks like sourcing, screening, due diligence, and asset monitoring.
Experience Building with Models, not just Building Models
Uses AI Every Day
Before you can revolutionize someone else’s workflow, you need to revolutionize yours. You should be using tools like ChatGPT, Cursor, Notebook LM, and Claude Code to accelerate your workflow.
Strong Programming and Data Analysis Skills
You need to have strong programming skills to be able to prove-out your ideas.
Biases Towards Showing vs. Telling
Our customers want to see the power of AI today vs discuss the most elegant idea that will take 5 years to realize.
We believe great Data Scientists come from diverse backgrounds and are unified by deep curiosity, pragmatism, and engineering excellence.
8+ years experience
A deep understanding of how to design and evaluate LLM-based applications
Ability to interpret statistical insights to non-technical or executive audiences
Strong programming skills

Nice-to-haves

Experience in financial systems, risk modeling, or decision automation
Familiarity with ML training and deployment
Experience with embedded analytics

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

llmaimachine learningreactml

Platform: gem
Effort: medium