Competitive Data Scientist

@ Great Value Hiring

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Canada

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Overview

Great Value Hiring is hiring a contract Competitive Data Scientist at $60 to $120 per hour. The role builds reproducible environments and reference solutions, writes tests and evaluation criteria, runs coding agents against tasks, and documents task requirements and verification steps.

Responsibilities:

Build reproducible environments and reference solutions
Develop tests and evaluation criteria
Run coding agents and investigate failures
Identify implementation errors and data leakage
Document task requirements and verification steps

Requirements summary:

Demonstrated experience in data science or ML
Experience in research competitions such as Kaggle or DrivenData
Strong problem-solving ability
Practical programming ability to implement and verify solutions
Strong Python coding experience (asset)

Tools & skills

Python Kaggle DrivenData Zindi AIcrowd Numerai DataSource.ai CodaLab/Codabench

Source and dates

Source type not verified · apify-linkedin

Employer posting date: 2026-11-03
First seen by our source: 2026-11-10
Source record updated: 2026-11-10

These dates describe the source record, not a live verification that the employer is still hiring. Check the original posting.

Job details

Travel	air: none · ground: none
Work setting	Home
Position	Mostly sitting
Physical demands	physical low · computer high

Summary and details written by AI from the posting; the employer’s posting is the authority.

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Great Value Hiring

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Field	Value
Open jobs on Jobsy	2

Job description

Competitive Data Scientist [$60 - $120/hour]

Role Responsibilities

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

Good Candidature

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.

Nice to Have

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