Offer summary

Qualifications:

Master's degree in Data Science, Computer Science, Biostatistics, or related field., Proven experience with clinical or biomedical data in healthcare research., Proficiency in Python, R, or SQL, with strong data manipulation and visualization skills., Experience with machine learning, natural language processing, and big data technologies..

Key responsibilities:

Collaborate with healthcare teams to design data science solutions for clinical research.

Analyze complex clinical datasets using advanced statistical and ML techniques.

Develop predictive models and extract insights from unstructured data using NLP.

Create visualizations and dashboards to communicate research findings effectively.

Job description

Vitalief – Where Innovation Meets Impact
Vitalief is redefining how clinical trials and research are conducted. As a Consulting and Functional Service Provider (FSP), we serve as trusted partners to research sites, sponsors, and CROs—streamlining operations, reducing costs, and accelerating scientific breakthroughs that improve patient lives.

Position Summary
This is a part-time job - just 10 hours per week, and the work can be performed outside normal business hours. This position is ideal for a person that wants to keep their full-time job and earn additional money. We are seeking a highly skilled and motivated Clinical Research Data Scientist to join our clinical research team. This individual will play a pivotal role in leveraging data to support clinical research, improve patient outcomes, and inform healthcare policy. The ideal candidate will work collaboratively with healthcare providers, scientists, and policymakers to ensure that data-driven insights are integrated at every stage of our research projects.

Work Location: 100% remote (must currently live in the USA) – our client is based in New Jersey.
Contract Duration: 6 months.
Hourly Pay Rate: Market Competitive – depending on experience level.

Responsibilities:

Collaborate with clinicians, researchers, and cross-functional teams to design and implement data science solutions that advance clinical research goals.
Analyze large and complex clinical datasets using advanced statistical methods.
Develop predictive models and apply machine learning (ML) techniques to identify patterns, biomarkers, or risk factors in patient data.
Create visualizations and dashboards that effectively communicate complex findings to both technical and non-technical stakeholders.
Conduct data cleaning, preprocessing, and transformation to prepare datasets for analysis.
Apply Natural Language Processing (NLP) to extract insights from unstructured data such as clinical notes and patient narratives.
Work with large-scale healthcare data environments using big data frameworks and cloud computing platforms.
Ensure data integrity, security, and compliance with HIPAA and other relevant regulations.
Stay current with emerging technologies and methodologies in the data science and healthcare domains.

Required Skills & Qualifications:

Master’s degree in Data Science, Computer Science, Biostatistics, Bioinformatics, or a related field.
Proven experience working with clinical or biomedical data in a research or healthcare setting.
Proficiency in statistical analysis and mathematics.
Advanced programming skills in Python, R, or SQL; experience with software engineering best practices is a plus.
Expertise in data manipulation and visualization tools (e.g., Pandas, Matplotlib, Seaborn, Tableau, Power BI).
Hands-on experience with machine learning, AI, and deep learning frameworks (e.g., scikit-learn, TensorFlow, PyTorch).
Knowledge of NLP techniques and libraries (e.g., spaCy, NLTK, transformers).
Familiarity with big data technologies (e.g., Hadoop, Spark) and cloud platforms (e.g., AWS, GCP, Azure).
Strong problem-solving skills and the ability to work independently and collaboratively.
Excellent communication skills to present findings clearly to non-technical stakeholders.