Description review
Competitive Data Scientist
micro1 · Remote · back to the listing
HR standards
67/100
needs work
Title ↔ description
50/100
needs work
Reads as
Data Scientist
89% confident
What this role officially is
data scientist — ESCO, the EU occupation classification
Data scientists find and interpret rich data sources, manage large amounts of data, merge data sources, ensure consistency of data-sets, and create visualisations to aid in understanding data. They build mathematical models using data, present and communicate data insights and findings to specialists and scientists in their team and if required, to a non-expert audience, and recommend ways to apply the data.
Also known as: data scientists, data engineer, research data scientist, data expert, data research scientist
How others title the same work
Large employers
- Data Scientist - Algorithms, Community Support Airbnb
- Data Scientist - Inference, Community Support Airbnb
- Senior Data Scientist, Guest & Host Airbnb
- Senior Data Scientist, Trust (Inference) Airbnb
- Data Scientist, Analytics (Technical Leadership) Meta
Startups
- Amplify Renewables | Quantitative Researcher | SF / Seattle / US | Hybrid (Remote Possible) | Full-Time | $200k - $375k (all cash) Amplify Renewables
- Senior Data Scientist BoldVoice
- Senior Research Neuroscientist ANORIA
- Quantitative Associate Corgi Insurance
- Senior Data Scientist Coulomb AI
What the listing never says
- No pay range published. Candidates cannot tell whether applying is worth their time. Pay transparency
The listing, marked up
Nothing in the wording of this listing tripped a check. The scores above still judge how complete and coherent it is.
Role Title: Competitive Data Scientist
Pay: $60–$120/hour
Location: Global, fully remote
Job Type: Contractor (~15 hours per week)
Schedule: Flexible-you choose the hours and days you work, including weekends if desired
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
• Build reproducible environments, prepare relevant data and dependencies, and implement reference solutions.
• Develop tests and evaluation criteria that reliably distinguish correct solutions from incomplete or flawed approaches.
• Run coding agents against tasks, investigate their failures, and refine the tasks based on observed behavior.
• Identify implementation errors, flawed assumptions, data leakage, and other issues that affect correctness.
• Document task requirements, solution reasoning, and verification steps clearly.
What We’re Looking For
• Demonstrated experience in data science, ML, quantitative modeling, or relevant research competitions. (Kaggle, DrivenData, etc.)
• Strong problem-solving ability and a clear understanding of the methods you use.
• 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
• Strong coding experience, particularly in Python, including testing, debugging, and working with unfamiliar code
Originally posted on Himalayas
Pay: $60–$120/hour
Location: Global, fully remote
Job Type: Contractor (~15 hours per week)
Schedule: Flexible-you choose the hours and days you work, including weekends if desired
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
• Build reproducible environments, prepare relevant data and dependencies, and implement reference solutions.
• Develop tests and evaluation criteria that reliably distinguish correct solutions from incomplete or flawed approaches.
• Run coding agents against tasks, investigate their failures, and refine the tasks based on observed behavior.
• Identify implementation errors, flawed assumptions, data leakage, and other issues that affect correctness.
• Document task requirements, solution reasoning, and verification steps clearly.
What We’re Looking For
• Demonstrated experience in data science, ML, quantitative modeling, or relevant research competitions. (Kaggle, DrivenData, etc.)
• Strong problem-solving ability and a clear understanding of the methods you use.
• 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
• Strong coding experience, particularly in Python, including testing, debugging, and working with unfamiliar code
Originally posted on Himalayas