AI Engineer

Michael Page - Development of predictive models for risk - Activities: Design and develop machine learning (ML) models to predict the risk of claims, the probability of fraud or optimize the determination of premiums. - Technologies: - ML libraries: Scikit-learn, XGBoost, LightGBM, TensorFlow, PyTorch. - Data Science tools: Pandas, NumPy, Matplotlib, Seaborn for data analysis and visualization. - Deep learning frameworks: Keras, TensorFlow, PyTorch. - Development of algorithms for personalized insurance policies - Activities: Create AI models and suggest customized policies based on their historical data and preferences. - Technologies: - Machine learning: Collaborative filtering for recommendations, linear and logistic regression, clustering (e.g., k-means, DBSCAN). - Dynamic pricing algorithms: Models based on decision trees or neural networks to calculate insurance premiums in real-time. - Automation and claims analysis - Activities: Build AI systems for automatic claim analysis, to speed up the approval process, identify fraud or optimize workflow management. - Technologies: - Convolutional neural networks (CNN): For image processing and recognition (e.g., damage assessment from photos). - NLP (Natural Language Processing): SpaCy, NLTK, transformers for automatic description analysis of claims or extracting information from textual documents. - OCR (Optical Character Recognition): Tesseract or Google Cloud Vision API for text extraction from scanned documents. - Fraud prevention - Activities: Create predictive models based on AI to identify suspicious and fraudulent claims. - Technologies: - Deep learning: Autoencoders for anomaly detection. - Classification models: Random Forest, SVM (Support Vector Machine), Gradient Boosting. - Anomaly detection techniques: Analysis of suspicious transactions through clustering or anomaly detection. 3 years of experience as an AI Engineer Excellent knowledge of Python ML libraries: Scikit-learn, XGBoost, LightGBM, TensorFlow, PyTorch. Data Science tools: Pandas, NumPy, Matplotlib, Seaborn Deep learning frameworks: Keras, TensorFlow, PyTorch. Insurtech company, main office in London 50 employees Full remote opportunity Contract indefinite with adequate pay based on experience Comprehensive insurance policy Full remote Excellent growth opportunities Sector: Other Role: Other