Simon Alibert

Building 🤗 LeRobot, Hugging Face's state-of-the-art Machine Learning library for real-world robotics.

• For a commercial vehicles rental company, I carried out an audit of pricing data and developed a pricing engine for pricing strategies optimization. • For a nutrition startup, I developed and deployed a recommender system based on users' preferences to provide the most relevant recipes in the app's feed.

Actuarial Analyst in the Life - Insurance, Consulting & Technology team. • Modeling: Transformed and optimized models for leading insurance companies, including migration and annualization of calculations. Reviewed IFRS and Solvency 2 calculations for a European insurer. • Production: Produced Statutory and Solvency 2 figures for a French Life Reinsurer. Conducted reviews and documented BEL calculation processes for major reinsurers. • Additional Responsibilities: Reserving using P&C methods, project management, budget follow-up, client interactions, and participation in IFRS17 working groups. • Software & Computing: Proficient in MoSes, RiskAgility FM, C++, SQL, VBA, and R.

• Study of implementation and calibration of LSMC polynomials in a standard formula approach in the context of tracking risk budgets' consumption, prospective solvency ratios and in response to permanent regulatory compliance requirements (Pillars I & II, ORSA) • State of the art of fast valuation methods for liabilities (screening procedures, curve fitting, replicating portfolio) • Research & Development through my actuarial master’s thesis: "Economic capital within the ORSA framework, Least Square Monte Carlo for life insurance" • I also helped the automation and improvement of the proxies validation process

• Financial production field mapping of the diversification assets in a low-rate environment • Reporting to support decision-making in arbitrage and disposal of unrealised gains processes, market-data extraction and analysis via Bloomberg • Regulatory watch

• Member of the Institute of Actuaries of France (IAA full member association) • Majors: parametric statistics, financial mathematics, Life and P&C modelling, stochastic processes, Asset-Liability management, law and regulations

Completed a 4-month full-time bootcamp (500+ hours) focusing on Machine Learning, Deep Learning, and DevOps. • Machine Learning: Data processing, feature engineering, supervised and unsupervised learning, model optimization, and interpretability. • Deep Learning: Multilayer perceptron, convolutional neural networks, NLP, recurrent neural nets, and transformers. • DevOps: SQL & NoSQL, CI/CD, cloud computing, Docker, Kubernetes, and model lifecycle management. • Projects: Churn prediction for a bank, galaxy morphology classification using deep neural nets, and full production deployment of the churn prediction project.