Overview
Remote
60 - 100
Contract - Independent
Contract - 1 Month(s)
No Travel Required
Unable to Provide Sponsorship
Skills
Analytics
Data Science
Data Analysis
Statistics
Machine Learning (ML)
Job Details
At Crossing Hurdles, we work as a referral partner. We refer candidates to our partner that collaborates with world’s leading AI research labs to build and train cutting-edge AI models.
Organization: Mercor
Position: Exceptional Data Scientists
Referral Partner: Crossing Hurdles
Type: Hourly contract
Compensation: $60–$100 per hour
Location: Remote
Duration: Minimum 1 month, with potential extension
Commitment: 10-40 hours/week, flexible and asynchronous
Responsibilities: (Training support will be provided)
- Design experiments, gather and preprocess data, build and evaluate models.
- Collaborate closely with engineering teams to deploy production-ready solutions.
- Write, review, and validate prompt-based questions used to train AI systems.
- Work proficiently in Python and Jupyter Notebooks.
- Utilize machine learning frameworks like TensorFlow or PyTorch.
- Analyze large datasets and build predictive models.
Requirements:
- Strong professional experience in data science or applied analytics.
- Highly skilled in Python and Jupyter Notebooks.
- Experience with libraries including numpy, pandas, scipy, sympy, scikit-learn, torch, tensorflow.
- Bachelor’s degree in data science, statistics, computer science, or related field
- Strong background in exploratory data analysis, statistical inference, machine learning workflows, model evaluation, feature engineering, data preprocessing, A/B testing, and causal inference.
- Excellent verbal and written communication skills.
- Strong attention to detail.
Application process: (Takes 20 min)
- Upload resume
- AI interview based on your resume (15 min)
- Submit form
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.