

JSR Tech Consulting
AI/ML Associate - REMOTE
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Junior Full Stack Data Scientist specializing in computational biophysics and machine learning, offering a remote contract. Pay rate is unspecified. Candidates need a Bachelor's in a relevant field, Python proficiency, and experience in healthcare or bioinformatics.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
Unknown
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🗓️ - Date
April 23, 2026
🕒 - Duration
Unknown
-
🏝️ - Location
Remote
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📄 - Contract
Unknown
-
🔒 - Security
Unknown
-
📍 - Location detailed
United States
-
🧠 - Skills detailed
#Scala #Scripting #PyTorch #SQL (Structured Query Language) #Flask #Data Manipulation #Visualization #Mathematics #ML (Machine Learning) #Deep Learning #Bash #Programming #Data Processing #Computer Science #AI (Artificial Intelligence) #HTML (Hypertext Markup Language) #Matlab #NumPy #Linux #Data Science #Python #MongoDB #C++ #Datasets
Role description
Job Title: Junior Full Stack Data Scientist – Computational Biophysics & Machine Learning
Location: Remote
Level: Entry to Junior About the Role
We are seeking a highly motivated Junior Full Stack Data Scientist to join our innovative team focused on healthcare, computational biophysics, biological system modeling/simulation, and machine learning. You will work closely with senior team members on high-performance, computationally intensive algorithms and help optimize them for better performance and scalability.
This is a unique opportunity to gain hands-on experience across data science, software engineering, and domain-specific modeling in a cutting-edge interdisciplinary environment. Key Responsibilities
• Write clean, efficient, and well-documented Python code for algorithm development and data processing.
• Assist in optimizing highly complex, computational algorithms used in simulations and modeling of biological systems.
• Collaborate on the development and maintenance of full stack data applications and visualization tools.
• Work with large-scale datasets, especially in the healthcare and bioinformatics domain.
• Support the implementation of classical and deep learning models using Python-based frameworks.
• Help integrate and analyze biological and clinical data using high-performance computing (HPC) techniques.
Highly Desired Qualifications
• Bachelor's degree in Computer Science, Data Science, Mathematics, or a related field is required.
• A Master's degree is a strong plus.
• Proficient in Python programming, especially for data manipulation, machine learning, and algorithm development.
• Ability to understand and work with complex algorithms and dynamic data structures.
• Exposure to machine learning frameworks (e.g., PyTorch, Scikit-Learn, NumPy).
• Experience or strong interest in bioinformatics, computational modeling, or scientific computing.
• Strong problem-solving skills and an eagerness to learn and grow in a collaborative environment.
Nice to Have
• Experience with SQL, C++, or MATLAB.
• Familiarity with front-end tools for visualization (HTML/CSS, D3.js).
• Exposure to full stack development (e.g., Flask, MongoDB).
• Prior work with Linux environments and scripting in Bash.
• Experience with HPC environments or parallel computing.
Work Environment
• Remote-friendly
• Collaborative, research-driven culture
• Focus on professional development and mentoring
If you're excited about solving meaningful problems at the intersection of healthcare, machine learning, and computational science, we encourage you to apply.
Job Title: Junior Full Stack Data Scientist – Computational Biophysics & Machine Learning
Location: Remote
Level: Entry to Junior About the Role
We are seeking a highly motivated Junior Full Stack Data Scientist to join our innovative team focused on healthcare, computational biophysics, biological system modeling/simulation, and machine learning. You will work closely with senior team members on high-performance, computationally intensive algorithms and help optimize them for better performance and scalability.
This is a unique opportunity to gain hands-on experience across data science, software engineering, and domain-specific modeling in a cutting-edge interdisciplinary environment. Key Responsibilities
• Write clean, efficient, and well-documented Python code for algorithm development and data processing.
• Assist in optimizing highly complex, computational algorithms used in simulations and modeling of biological systems.
• Collaborate on the development and maintenance of full stack data applications and visualization tools.
• Work with large-scale datasets, especially in the healthcare and bioinformatics domain.
• Support the implementation of classical and deep learning models using Python-based frameworks.
• Help integrate and analyze biological and clinical data using high-performance computing (HPC) techniques.
Highly Desired Qualifications
• Bachelor's degree in Computer Science, Data Science, Mathematics, or a related field is required.
• A Master's degree is a strong plus.
• Proficient in Python programming, especially for data manipulation, machine learning, and algorithm development.
• Ability to understand and work with complex algorithms and dynamic data structures.
• Exposure to machine learning frameworks (e.g., PyTorch, Scikit-Learn, NumPy).
• Experience or strong interest in bioinformatics, computational modeling, or scientific computing.
• Strong problem-solving skills and an eagerness to learn and grow in a collaborative environment.
Nice to Have
• Experience with SQL, C++, or MATLAB.
• Familiarity with front-end tools for visualization (HTML/CSS, D3.js).
• Exposure to full stack development (e.g., Flask, MongoDB).
• Prior work with Linux environments and scripting in Bash.
• Experience with HPC environments or parallel computing.
Work Environment
• Remote-friendly
• Collaborative, research-driven culture
• Focus on professional development and mentoring
If you're excited about solving meaningful problems at the intersection of healthcare, machine learning, and computational science, we encourage you to apply.






