Jean Lescut-Müller

Jean Lescut-Müller

Data Scientist (part-time consultant)

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location of Jean Lescut-MüllerZurich, Zurich, Switzerland

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  • Timeline

  • About me

    Lead Data Scientist

  • Education

    • Columbia University in the City of New York

      2012 - 2013
      MSc Management Science & Engineering

      This 4-semester, 12-course program, offered by the IEOR (Industrial Enginnering & Operations Research) Department in conjunction with Columbia Business School, emphasizes both management and engineering perspectives in : Machine Learning, Decision Making, Advanced Mathematics and Statistics, and Project Management

    • Columbia Business School

      2012 - 2013
      Master's degree Management Science & Engineering

      Business Analytics Strategy, Quantitative Pricing & Revenue Analytics, Corporate Finance & Accounting, HR management

    • CentraleSupelec

      2010 - 2013
      Engineer's degree Engineering GPA : 3.9/4

      Activities and Societies: Students Representative (elected twice in 2010 & 2011), campus band (drum player) Engineering degree of the top 3 prestigious French “Grandes Ecoles”

  • Experience

    • Columbia University in the City of New York

      Sept 2012 - Aug 2013
      Data Scientist (part-time consultant)

      Among other clients, FreshDirect : - Proposed and Designed an algorithm based on Genetic Algorithm to optimize inventory placement - Analysed results and presented recommendations to client, reducing picking time (the main source cost) by 5%.

    • Talan

      Oct 2013 - Mar 2014
      Data Scientist (Consultant)

      Scoping of the project about optimising network for a transporter: dispatch and schedule pickups and deliveries of goods in the most efficient way as possible

    • EY

      Mar 2015 - Sept 2016

      Numerous mission for various clients, including (but not limited to) :- L'Oreal (Data Science for R&D of new products) 1) Responsible of a project to predict microbiological sterility of products. Proposed, designed, implemented a machine learning model, then monitored and maintained it in production. Managed stakeholders, communicated KPIs resulting in 30% decrease in cost of microbial tests. 2) Pitched and sold to the client a complete redesign or 1 of their product, shifting from R code to more modern technologies : Python & Spark Show less Numerous mission for various clients, including (but not limited to) :- Audit firm (HR Predictive Analytics)Framed, designed and implemented a predictive tool for employee departure using signals from social networks and Survival analysis- Boehringer-Ingelheim (Data Science for Marketing)Helped to establish a marketing plan : which pilot region to target and how to promote a new medical device. (Pharmacies clustering and elasticity estimation)- Multinational company in Telecommunication (Data Science for Marketing)Customers clustering (DBSCAN) and standard data analysis of survey (MFA, PCA, etc.) Flew abroad to present results to A-level executives Show less

      • Senior Data Scientist (Consultant)

        Dec 2015 - Sept 2016
      • Data Scientist (Consultant)

        Mar 2015 - Dec 2015
    • ITrust

      Sept 2016 - May 2017
      Lead Data Scientist

      Managed 4-member team to "stabilize" (and make ready for production) a Spark Streaming application used for Anomaly Detection in IT System, hence exposing intrusions or Cyber-threats like APTs. The team was composed of data scientists, backend and frontend developers, using Agile (scrum) methods

    • Expedia, Inc.

      May 2017 - Sept 2021
      Senior Data Scientist

      𝗜𝗻 𝗰𝗵𝗮𝗿𝗴𝗲 𝗼𝗳 𝗱𝗲𝘃𝗲𝗹𝗼𝗽𝗶𝗻𝗴 & 𝗰𝗼𝗮𝗰𝗵𝗶𝗻𝗴 𝟮 𝗱𝗮𝘁𝗮 𝘀𝗰𝗶𝗲𝗻𝘁𝗶𝘀𝘁𝘀 𝗼𝗳 𝘁𝗵𝗲 "𝗥𝗲𝘃𝗲𝗻𝘂𝗲 𝗢𝗽𝘁𝗶𝗺𝗶𝘇𝗮𝘁𝗶𝗼𝗻" 𝘁𝗲𝗮𝗺 𝗼𝗳 𝘁𝗵𝗲 𝗴𝗿𝗼𝘂𝗽 :ㅤ- Upstream of development :ㅤㅤ- Initiated numerous DS projects : proposal, framing, effort sizing, stakeholder management. - Culture : evangelising a "client-centric" vision through the group.ㅤ- Development :ㅤㅤ- Structure & methodology : data retrieval, EDA, cleaning, feature engineering, MVP, ㅤㅤ productionalization, progressive deployment, maintenance & monitoringㅤㅤ- task prioritisation, follow-ups, escalation, helped when needed, and sometimes more "hands-on"ㅤㅤㅤML training, and pair-coding for the most junior team memberㅤ- Downstream of ML development :ㅤㅤ- DevOps good-practice, help on deployment.ㅤㅤ- Design of monitoring framework & requirements, choice of tools𝗔𝘀 𝗮𝗻 𝗶𝗻𝗱𝗶𝘃𝗶𝗱𝘂𝗮𝗹 𝗰𝗼𝗻𝘁𝗿𝗶𝗯𝘂𝘁𝗼𝗿 :ㅤ- Daily tools : Python, Scala, Spark, Hive & Presto, AWS, Unix admin, among others.ㅤ- Consumer demand forecasting (Bayesian auto-regressive model), by products (hotel), and brands.ㅤㅤAutomatic retraining on a daily basis.ㅤ- Optimising online CVR by applying optimal discounts (based on price elasticity, predicted by ML)ㅤ- Anomaly detection (Monitoring & Alerting), currently applied to different projects.ㅤ- Harmonisation of KPI definition (customer LTV & retention KPIs) & stakeholder mediations Show less

    • Richemont

      Sept 2021 - Nov 2024
      Lead Data Scientist

      𝗣𝗿𝗼𝗷𝗲𝗰𝘁 𝗔 (𝗰𝗼𝗻𝗳𝗶𝗱𝗲𝗻𝘁𝗶𝗮𝗹, 𝗱𝗼𝗻𝗲 𝗳𝗼𝗿 𝟭 𝗠𝗮𝗶𝘀𝗼𝗻 𝗼𝗳 𝘁𝗵𝗲 𝗴𝗿𝗼𝘂𝗽) :ㅤ- Tech Lead in a 4-member team (including 1 DS intern, 1 Data analyst, and 1 Business Analyst) aiming ㅤㅤat clustering website visitors, and predicting client LTV & conversion probability. ㅤ- Client activations in 3 steps : worked closely with Richemont Marketing for CRM Activation,ㅤㅤRichemont Media for Media activation, and with Group Tech for Website Activation.𝗣𝗿𝗼𝗷𝗲𝗰𝘁 𝗕 (𝗰𝗼𝗻𝗳𝗶𝗱𝗲𝗻𝘁𝗶𝗮𝗹, 𝗱𝗼𝗻𝗲 𝗳𝗼𝗿 𝟭 𝗠𝗮𝗶𝘀𝗼𝗻 𝗼𝗳 𝘁𝗵𝗲 𝗴𝗿𝗼𝘂𝗽) :ㅤ- Tech Lead for a 4-member team (including 1 Data Scientist, 1 ML Engineer, 1 FE dev) to develop aㅤㅤDash-based web app forecasting demand and optimising client satisfaction. Show less

  • Licenses & Certifications

    • Deep Learning, by Pr. Nando de Freitas, Oxford

      Coursera
      Feb 2016
    • Machine Learning, by Pr. Andrew Ng, Stanford

      Coursera
      Dec 2014