Competitive Data Scientist (Kaggle)

We're looking for data scientists, machine learning practitioners, and applied mathematics experts with competitve Data Science experience. (Kaggle, DrivenData, etc.)

You’ll draw on your competition experience, mathematical reasoning, and programming skills to create tasks that require more than a plausible answer. Each task should have a reproducible environment, a verified reference solution, and reliable checks for successful completion.

What You’ll Do

1. Build reproducible environments, prepare relevant data and dependencies, and implement reference solutions.
2. Develop tests and evaluation criteria that reliably distinguish correct solutions from incomplete or flawed approaches.
3. Run coding agents against tasks, investigate their failures, and refine the tasks based on observed behavior.
4. Identify implementation errors, flawed assumptions, data leakage, and other issues that affect correctness.
5. Document task requirements, solution reasoning, and verification steps clearly.

What We’re Looking For

1. Demonstrated experience in data science, ML, quantitative modeling, or relevant research competitions. (Kaggle, DrivenData, etc.)
2. Strong problem-solving ability and a clear understanding of the methods you use.
3. Practical programming ability sufficient to implement and verify your own solutions.

Relevant competition platforms include Kaggle, DrivenData, Zindi, AIcrowd, Numerai, DataSource.ai, and CodaLab/Codabench.

Huge Pluses

1. Strong coding experience, particularly in Python, including testing, debugging, and working with unfamiliar code

Schedule: Flexible-you choose the hours and days you work, including weekends if desired

About micro1

micro1 is a data lab that helps AI labs & Enterprises train foundational models and agents. We provide frontier evaluations and reinforcement learning environments to improve LLM capabilities, as well as contextual evaluations to monitor and improve AI agents in enterprise settings.Our AI recruiting agent sources and vets domain experts for our data platform that enables rapid production of high-quality training data. Our research spans high-value, specialized domains (legal, medical, finance, coding, etc.), where expert-level data is the hardest to produce and most valuable for advanced model performance. Our pipeline performance system ensures both quality and velocity.