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
Part-time (20 hrs - 40 hrs/week)
Weekly bonus of $500 - $1000 USD per 5 task created.
Contract and Payment Terms
You will be engaged as an independent contractor.
This is a fully remote role that can be completed on your own schedule.
Projects can be extended, shortened, or concluded early depending on needs and performance.
Your work at will not involve access to confidential or proprietary information from any employer, client, or institution.
Payments are weekly on Stripe or Wise based on services rendered.