Data Analyst | Remote

Crossing Hurdles; India; A distancia; INR 7.776.000 - 15.551.000; Jornada completa

Descripción de la vacante

Nextleap is seeking a Computational Bioscience Expert for a remote contract engagement. You will tackle scientifically rigorous problems, develop reproducible Python-based analyses, models, simulations, or data-processing workflows, and review solutions for correctness and clarity.

The role emphasizes strong life sciences experience and practical coding in Python with common scientific libraries. Candidates with publications or thesis work and demonstrated computational projects are encouraged

Formación

• Strong experience in a life sciences discipline.
• Publications, thesis work, or computational projects demonstrating research ability.
• Practical Python experience for scientific computing, data analysis, modeling or simulation.
• Familiarity with NumPy, pandas, SciPy, Matplotlib, scikit-learn, Jupyter or domain libs.

Responsabilidades

• Create and solve scientifically rigorous problems in your area of expertise.
• Develop reproducible Python-based analyses, models, simulations, or data-processing workflows.
• Review scientific solutions and code for correctness, clarity, and completeness.

Conocimientos

Life sciences experience

Publications

Academic thesis work

Computational projects

Herramientas

Python

NumPy

pandas

SciPy

Matplotlib

scikit-learn

Jupyter

Descripción del empleo

Position:

Computational Bioscience Expert

Type:

Contract

Compensation:

$60 - $120/hour

Location:

Remote

Commitment:

10-40 hrs/week

Role Responsibilities

• Create and solve technically rigorous scientific problems within your area of expertise.
• Develop reproducible Python-based analyses, models, simulations, or data-processing workflows.
• Review scientific solutions and code for correctness, clarity, and completeness.

Requirements

• Have strong relevant experience in a relevant life sciences discipline.
• Strong scientific or applied research background demonstrated through publications, thesis work, computational projects, or industry research.
• Practical Python experience for scientific computing, data analysis, modeling, or simulation.
• Familiarity with tools such as NumPy, pandas, SciPy, Matplotlib, scikit-learn, Jupyter, or relevant domain-specific libraries.