Data Scientist – AI/ML

The SpringCube team curated the following job opportunity to help you in your job search. Explore the position below to find your next career move.

Company Overview

A leading healthcare organization is advancing the use of Artificial Intelligence and Machine Learning to develop innovative solutions across patient care, medical research, and administrative services. Its Data Science team works closely with clinical specialists, researchers, and operational teams to introduce emerging AI and ML technologies into healthcare while maintaining strong standards for safety, ethics, quality, and cost effectiveness.

The organization is seeking a Data Scientist – AI/ML to contribute to the development and implementation of AI-powered healthcare solutions, ranging from predictive algorithms to agentic systems. Reporting to the Data Science Director and collaborating closely with senior data science leadership, the successful candidate will help develop, evaluate, deploy, and support machine learning solutions designed to improve patient outcomes and healthcare operations.

The Data Scientist will be part of a multidisciplinary team focused on bringing Artificial Intelligence, predictive algorithms, and emerging machine learning innovations into healthcare. The role will involve collaborating with clinical specialties, researchers, and operational teams to develop solutions that can be safely and effectively applied in clinical environments.

Key Responsibilities

• Build, deploy, and maintain AI- and ML-enabled healthcare workflows.
• Collaborate with internal stakeholders to identify problems and design data science solutions that address clinical and operational needs.
• Evaluate tools, platforms, and strategies used to manage the lifecycle of machine learning models built from healthcare data.
• Train, develop, and validate machine learning algorithms using hospital and healthcare datasets.
• Evaluate researcher-developed and vendor-provided machine learning algorithms for potential healthcare applications.
• Apply rigorous quality control processes when developing and validating machine learning models.
• Conduct bias assessments to help ensure AI solutions are safe, ethical, and appropriate for healthcare applications.
• Design, implement, and support machine learning models for use in clinical environments.
• Develop predictive algorithms and other AI-driven solutions that can contribute to improved patient outcomes.
• Work closely with clinicians and researchers across multiple disciplines to develop approaches suitable for clinical care.
• Contribute to the evaluation and implementation of emerging AI and machine learning technologies.
• Support the full lifecycle of AI and ML solutions, from development and validation through deployment and maintenance.

Required Qualifications

• PhD or Master’s degree in Statistics, Informatics, or a related field.
• Candidates with a PhD are preferred to have relevant experience.
• Candidates with a Master’s degree should have at least 4 years of related experience working with applied problems.
• Experience writing code in SQL, R, or Python for processing large datasets.
• Experience working with distributed cloud environments.
• Experience processing and analyzing healthcare data.
• Experience developing, evaluating, and implementing machine learning models.
• Experience collaborating with clinicians and researchers across disciplines.
• Experience working in cloud environments or within a healthcare organization.
• Graduate-level understanding of machine learning techniques, knowledge representation, and artificial intelligence.
• Strong understanding of statistics.
• Knowledge of software development, machine learning, and technology infrastructure.
• Excellent verbal and written communication skills.
• Strong interpersonal and collaboration skills.
• Demonstrated creativity and flexibility in solving complex problems.
• Ability to prioritize and execute multiple competing tasks effectively.

Disclaimer

SpringCube curates tech job listings from various company websites to support tech professionals globally.

1. No Endorsement: Job ads on SpringCube do not imply endorsement of their authenticity or quality.
2. No Client Relationship: This company is not a client of SpringCube unless stated.
3. To Apply: Click the Apply button to be redirected to the hiring company’s application page for this job.
4. No Liability: SpringCube is not liable for inaccuracies.