**hiring a Data Scientist** to help build advanced analytics and data\-driven infrastructure for its AI lab partner focused on developing intelligent agent\-based systems. This role is ideal for analytical thinkers who excel at turning large\-scale data into actionable insights and enjoy working at the intersection of machine learning, experimentation, and real\-world applications. You’ll be designing data pipelines, statistical models, and performance metrics that drive the next generation of autonomous systems. **You’re a great fit if you:** ------------------------------ * Have a strong background in **data science, machine learning, or applied statistics**. * Are proficient in **Python, SQL**, and familiar with libraries such as **Pandas, NumPy, Scikit\-learn, and PyTorch/TensorFlow**. * Understand **probabilistic modeling, statistical inference, and experimentation frameworks (A/B testing, causal inference)**. * Can **collect, clean, and transform complex datasets** into structured formats ready for modeling and analysis. * Have experience designing and evaluating **predictive models**, using metrics like precision, recall, F1\-score, and ROC\-AUC. * Are comfortable working with **large\-scale data systems** (Snowflake, BigQuery, or similar). * Are curious about **AI agents**, and how data can shape the reasoning, adaptability, and behavior of intelligent systems. * Enjoy **collaborating with cross\-functional teams** — from engineers to research scientists — to define meaningful KPIs and experiment setups. **Primary Goal of This Role** ----------------------------- To design and implement robust data models, pipelines, and metrics that support experimentation, benchmarking, and continuous learning for agentic AI systems. The role focuses on building data\-driven insights into how agents reason, perform, and improve over time across algorithmic and real\-world tasks. **What You’ll Do** ------------------ * Develop **data collection and preprocessing pipelines** for structured and unstructured data from multiple agent simulations. * Build and iterate on **machine learning models** for performance prediction, behavior clustering, and outcome optimization. * Design and maintain **dashboards and visualization tools** for monitoring agent performance, benchmarks, and trends. * Conduct **statistical analyses** to evaluate the efficacy of AI systems under various environments and constraints. * Collaborate with engineers to design **evaluation frameworks** that measure reasoning quality, adaptability, and efficiency. * Prototype **data\-driven tools and feedback loops** to automatically improve model accuracy and agent behavior over time. * Work closely with AI research teams to **translate experimental results** into scalable, production\-grade insights. **Why This Role Is Exciting** ----------------------------- * Work at the forefront of **AI agent intelligence** and help define how data shapes their evolution. * Blend **machine learning, experimentation, and data engineering** in one role. * Collaborate with top\-tier AI engineers on **new agent benchmarks and feedback mechanisms**. * Contribute to a mission that merges **algorithmic reasoning, real\-world performance, and human\-like decision\-making**. **Pay \& Work Structure** ------------------------- * You’ll be classified as an **hourly contractor** to. * **Paid weekly** via Stripe Connect, based on hours logged. * **Part\-time (20 hrs \- 40 hrs/week)** with fully remote, async flexibility — work from anywhere, on your own schedule. * Weekly bonus of $500 \- $1000 USD per 5 task created.