Data Scientist – Machine Learning, AI

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Cyntegrity

WebsiteLinkedInAll Job Openings

51 - 200 employees

Founded 2014

🤖 Artificial Intelligence

⚕️ Healthcare Insurance

💊 Pharmaceuticals

Artificial Intelligence • Healthcare Insurance • Pharmaceuticals

Cyntegrity is a company that provides AI-augmented risk-based quality management (RBQM) solutions for clinical trials. Their integrated solutions enhance operational efficiency through a comprehensive risk management approach, helping optimize clinical operations while ensuring compliance and reducing costs. With a focus on data quality and patient safety, Cyntegrity's MyRBQM Portal offers predictive analytics, decentralized clinical trial support, and educational resources to foster a quality-by-design culture. Their tools and methodologies are designed to address current regulatory guidelines and are trusted by many global organizations in the biopharmaceutical sector.

📋 Description

• Design, develop, and validate statistical, machine learning, and AI models • Build and evaluate Proofs of Concept (PoCs) for new analytical solutions • Analyze complex clinical trial data to identify patterns, risks, and insights • Collaborate with Product, Engineering, Clinical Monitoring, and customer-facing teams to transform business challenges into analytical solutions • Develop production-ready analytical components together with software engineers • Present findings through clear visualizations and communicate results to both technical and non-technical stakeholders • Continuously explore new technologies and contribute innovative ideas to our products

🎯 Requirements

• Bachelor's degree in Data Science, Statistics, Mathematics, Computer Science, Engineering, Physics, or another quantitative field • 3+ years of professional experience using Python and/or R for statistical analysis and machine learning • Hands-on experience building, validating, and improving predictive models • Experience designing and executing analytical or machine learning Proofs of Concept • Experience with clinical research or healthcare data is a strong advantage • Strong understanding of statistics, hypothesis testing, regression, feature engineering, and model validation • Practical experience with machine learning and AI techniques • Ability to communicate complex ideas clearly to different audiences • Familiarity with software engineering best practices, version control, testing, and reproducible analytical workflows • Understanding of GCP, clinical trial processes, or risk-based quality management is a plus • Nice to have: Experience with cloud-based analytics environments (Azure, AWS, Databricks, Snowflake) • Nice to have: Experience with modern ML frameworks such as scikit-learn, XGBoost, TensorFlow, or PyTorch

🏖️ Benefits

• Fully remote work with flexible working hours • An international, collaborative, and supportive team • High level of autonomy and ownership • Professional growth and continuous learning opportunities • A purpose-driven environment where your work has real impact