Junior Data Scientist | Healthcare AI & Analytics

Company and Role Overview

Work Environment

• The role is part of a remote team in a remote-first environment.
• The position offers fully remote work with a flexible working environment and autonomy.

Accountabilities

• Analyze clinical, operational, and patient datasets to identify meaningful insights and trends.
• Build, test, and improve machine learning models for predictive healthcare applications.
• Perform exploratory data analysis and statistical analysis to support business decisions.
• Develop dashboards, reports, and visualizations using modern business intelligence tools.
• Clean, prepare, validate, and transform structured and unstructured datasets.
• Support AI-powered healthcare initiatives and predictive analytics projects.
• Collaborate with software engineers and product teams to deploy data-driven solutions.
• Improve data quality, reliability, and analytical workflows.
• Automate recurring reporting and data analysis processes.
• Document methodologies, experiments, and analytical findings.
• Stay informed about emerging data science, artificial intelligence, and machine learning technologies.

Required Qualifications and Skills

• Bachelor’s degree in Computer Science, Data Science, Mathematics, Statistics, Biomedical Engineering, Health Informatics, or a related field.
• Up to two years of relevant experience, or strong personal projects demonstrating analytical skills.
• Strong programming skills in Python and SQL.
• Understanding of machine learning algorithms, predictive modeling, and statistical analysis.
• Familiarity with Power BI, Tableau, or Looker for data visualization.
• Experience with structured datasets and data cleaning techniques.
• Strong analytical thinking and problem-solving skills.
• Good written and verbal English communication skills.
• Passion for AI, machine learning, healthcare technology, and continuous learning.

Preferred Qualifications

• Experience working with healthcare data or Electronic Health Records is preferred.
• Familiarity with AWS, Azure, or Google Cloud Platform is preferred.
• Knowledge of APIs and large-scale datasets is preferred.
• Kaggle competitions, bootcamp projects, GitHub portfolios, or personal data science projects are preferred.
• Exposure to Generative AI or Large Language Models is a plus.

Benefits

• Opportunity to work on real-world healthcare AI and machine learning projects.
• Exposure to predictive analytics, healthcare technology, and modern data science tools.
• Collaborative international team environment.
• Continuous professional development and learning opportunities.
• Career progression within a growing organization.
• Competitive compensation based on experience.