Noah Sultan

- Automation (dbt, git, airflow) - Price elasticity & Revenue Growth Management (RGM) - Customer Segmentation (rule-based, supervised multi class classification, unsupervised) - BI and streamlit (front end reporting)

▪ Measurement of CRM, clienteling, and media impact on customer behavior ▪ Delivered MMM models quantifying the contribution of CRM and clienteling activities to customer reactivation ▪ Built automated monitoring tools with dbt & Looker → significant reduction in reporting and analysis time ▪ Conducted customer-journey analyses to optimize CRM and marketing activations Tools : Python, SQL, GCP, Git, Excel, Looker, Salesforce SC, SF Marketing Cloud, Visual Studio, SAP BI, LookML. About the group : Van Cleef & Arpels is a subsidiary of Richemont Group which possess an elite community of ML engineers and data scientists. The group provides an environment that encourages implementing AI & ML best practices.

▪ Evaluation of digital channels and their contribution to conversions ▪ Developed MMM models measuring the impact of Meta, Google Ads, display, and CRM channels on web conversions and ROI ▪ Supported client digital transformation through automation pipelines and strategic, data-informed recommendations Tools : Python, SQL, and Power BI.

Responsible for developing artificial intelligence (AI) solutions and machine learning (ML) algorithms to improve the software developed by the company. • Leading the research on the possible AI solutions. • Building data-driven models for prediction and approximation purposes. • Software developing and debugging in C# and Python. • Time series and Gaussian process. • Design of experiments (factorial & optimal designs). • Artificial neural networks. • Multi-objective optimization and Pareto efficiency. • Ensemble learning and random forests 🌳. • Stochastic algorithms (evolution strategy and genetic algorithm).

Managed a project, financed by the EU, where we have developed a new software for DNA motifs discovery, making use of genomic and transcriptomic data. • First-author publication in a peer-reviewed journal, (Pubmed) (DOI: 10.1098/rsif.2020.0600). • Exploratory analysis of Bayesian models, and data visualisation using R. • Statistical analysis (hypothesis testing), including the use of exploratory approaches of the multivariate analysis toolbox (clustering, multidimensional scaling). • Software developing and debugging in C++. Conference talks: JOBIM 2018. Journées Ouvertes Biologie, Informatique et Mathématiques. Marseille, France (Speaker)​​ JDS 2018. 50èmes Journées de Statistique. Palaiseau, France (Speaker)​​ International Symposium Foodborne pathogens: from farm to pharmacy 2018, Kinsale, Ireland (Speaker)​​ Computational approaches to nucleic acid and protein structure & function, JUNIOR CONFERENCE, University of Paris XI, 2017, Orsay, France​​ (Speaker)​​ FEMS Microbiology Congress 2017, Valencia, Spain (Speaker) ISOPOL XIX 2016. Paris, France Summer Schools: Making sense of transcriptomic data. July, 2016. Frankfurt, Germany Training on the potential and power of proteomics to address biological questions through a Systems Biology approach. July, 2017. Clermont-Ferrand, France Workshops: Scientific outreach (communicating scientific ideas to non-specialist public). Oct, 2015. Dijon, France Introduction to statistical analysis of expression data with R. Oct, 2016. Jouy-en-Josas, France Training on system biology. Oct, 2017. Copenhagen, Denmark Outreach activities: European Researchers Nights 2016 and 2017 An event that aims to bring researchers closer to the general public and to increase awareness of research and innovation activities.