Scientific Computing Expert | $16/hr Remote

Crossing Hurdles; India; On-site; INR 1,313,000 - 1,839,000; Part time

Job summary

Crossing Hurdles is seeking a Pod lead for Scientific Computing / Research Engineering Expert on a remote, contractor basis. Start date is immediate, with a commitment of 10-40 hours per week and compensation at $12 per hour.

The role emphasizes designing terminal-based scientific tasks, validating computations with real datasets, and delivering reproducible workflows. Candidate should have advanced Earth Sciences expertise and strong programming skills (Python, R, Bash, Julia), plus

Qualifications

• Advanced technical experience in Earth Sciences or related disciplines.
• Proficient in Python, R, Bash or Julia.
• Hands-on experience with Linux and terminal-based environments.
• Expertise in scientific data processing and geospatial analysis.
• Knowledge of spatial datasets, time-series analysis, and data quality control.
• Ability to develop and validate reproducible scientific workflows with real-world datasets.

Responsibilities

• Design and develop terminal-based scientific tasks for AI training.
• Validate computational tasks using scientific datasets.
• Conduct geospatial analysis and numerical modeling.
• Develop reproducible computational workflows.

Skills

Earth Sciences

Python

R

Bash

Julia

Linux

Terminal

Tools

Linux

Terminal

Job description

Position: Pod lead - Scientific Computing / Research Engineering Expert

Type: Contractor

Compensation: $12 per hour

Location: Remote

Commitment: 10-40 hrs/week

Start Date: Immediately

Role Responsibilities

• Design and develop terminal-based scientific tasks for AI training.
• Validate computational tasks using scientific datasets.
• Conduct geospatial analysis and numerical modeling.
• Develop reproducible computational workflows.

Requirements

• Possess advanced technical experience in Earth Sciences or related disciplines.
• Demonstrate strong programming skills in Python, R, Bash, or Julia.
• Have hands-on experience with Linux and terminal-based environments.
• Show expertise in scientific data processing and geospatial analysis.
• Understand spatial datasets, time-series analysis, and data quality control.
• Develop and validate reproducible scientific workflows with real-world datasets.