Data Scientist | $100/hr Remote | Mercor

Crossing Hurdles; United Kingdom; Remote; GBP 61,984 - 103,307; Part time

Job summary

A referral partner for AI projects is seeking an experienced Data Scientist to work remotely. This hourly position pays up to $100/hr based on skills and experience. You will focus on hands-on tasks such as data preprocessing, model building, and collaborating with engineering teams to deploy solutions. Ideal candidates should have a strong background in data science, proficiency in Python, and familiarity with libraries like numpy and pandas. The role offers flexible hours, approximately 10-40 hours per week, and is expected to last about two months, with extensions possible.

Qualifications

• Strong professional experience in data science or applied analytics.
• Skilled in Python and Jupyter notebooks.
• Experience using libraries like numpy, pandas, scipy.

Responsibilities

• Focus on hands-on data science tasks, such as designing experiments.
• Gathering and pre-processing data.
• Building and evaluating models, collaborating closely with engineering teams.

Skills

Data science

Python

Jupyter notebooks

Machine learning workflows

Data preprocessing

Job description

Data Scientist | $100/hr Remote | Mercor

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This range is provided by Crossing Hurdles. Your actual pay will be based on your skills and experience—talk with your recruiter to learn more.

Base pay range

$60/hr - $100/hr

At Crossing Hurdles, we work as a referral partner. We refer candidates to Mercor that collaborates with world’s leading AI research labs to build and train cutting‑edge AI models.

Organization: Mercor

Position: Data Scientist

Referral partner: Crossing Hurdles

Type: Hourly Contract

Compensation: $60-$100/hour

Location: Remote

Duration: Approximately 2 months (extension feasible)

Commitment: 10‑40 hours per week, fully asynchronous

Role Responsibilities

• Focus on hands‑on data science tasks, such as designing experiments
• Gathering and pre‑processing data
• Building and evaluating models, and collaborating closely with engineering teams to deploy production‑ready solutions
• Ensure output consistency and quality through collaboration with peers and feedback from reviewers

Ideal Qualifications

• Strong professional experience in data science or applied analytics
• Skilled in Python and Jupyter notebooks
• Experience using libraries including numpy, pandas, scipy, sympy, scikit‑learn, torch, tensorflow
• Strong background in one or more of the following areas: exploratory data analysis and statistical inference, machine learning workflows and model evaluation, feature engineering/data preprocessing/data wrangling, or A/B testing/experimentation/causal inference

Application Process

• Upload resume
• AI interview based on your resume (15 min)