Senior Data Scientist at Société Générale with experience leading data science projects end-to-end, including requirement gathering, data preparation, feature engineering, implementation, and monitoring. Has built predic…
Senior Data Scientist at Société Générale with experience leading data science projects end-to-end, including requirement gathering, data preparation, feature engineering, implementation, and monitoring. Has built predictive and prescriptive analytics models such as recommendation systems, churn models, customer segmentation, customer lifetime value, fraud detection, and NLP/deep learning classifiers. Holds a Master of Science in Data Science & Big Data from Institut Polytechnique de Paris / Telecom SudParis.
- Led a team of data scientists to design, prototype, implement and test predictive and prescriptive analytic models like product recommendation system, churn modeling, customer segmentation and customer life time value
- Worked with business teams to identify critical business problems and opportunity areas and translate business questions into quantitative analyses
- Led Data Science projects during all phases of the development life cycle including requirement gathering and analysis, data preparation, data featuring, implementation and monitoring
- Worked with cross-functional partners in product, engineering, marketing, and operations to achieve business goals
Performed feature selection from over 1500 features using Population Stability Index and CMIM Provided analytic insights and advice to maximize the business impact
- Conceptualized and architected a predictive model to accurately predict the customer likelihood of consumer credit subscription on the website
<p>Led a team of data scientists to design, prototype, implement and test predictive and prescriptive analytic models like product recommendation system, churn modeling, customer segmentation and customer life time value<br>
Worked with business teams to identify critical business problems and opportunity areas and translate business questions into quantitative analyses<br>
Led Data Science projects during all phases of the development life cycle including requirement gathering and analysis, data preparation, data featuring, implementation and monitoring<br>
Worked with cross-functional partners in product, engineering, marketing, and operations to achieve business goals<br>
Performed feature selection from over 1500 features using Population Stability Index and CMIM<br>
Provided analytic insights and advice to maximize the business impact<br>
Conceptualized and architected a predictive model to accurately predict the customer likelihood of consumer credit subscription on the website<br>
Performed DBSCAN clustering to understand customer backgrounds and segment the customers based on their transaction behavior for customized product offering<br>
Built and industrialized fraud classifier model to detect dangerous emails (phishing, scam, spam) using Word2Vec and Natural Language Processing<br>
Built classification models on customer review comments and email data using Latent Dirichlet allocation and Deep learning algorithms like CNN, RNN and LSTM<br>
Assisted Data Scientist to build Auto-encoder Deep Learning model to detect application shutdown</p>
<p>Participated in Entrepreneurship Program to create a real estate digital startup in Schoolab incubator<br>
Conducted interviews, conceptualized, and built product prototype to meet customer needs<br>
Managed end-to-end process including observation, growth hacking, client acquisition and A/B testing</p>
<p>Audited critical platforms of a telecommunication operator<br>
Created risk cartographies related to the data center and call center of the operator and followed the risk mitigation plan<br>
Performed interviews with relevant process owners and executives within Technical Direction</p>
- Performed DBSCAN clustering to understand customer backgrounds and segment the customers based on their transaction behavior for customized product offering
- Built and industrialized fraud classifier model to detect dangerous emails (phishing, scam, spam) using Word2Vec and Natural Language Processing
- Built classification models on customer review comments and email data using Latent Dirichlet allocation and Deep learning algorithms like CNN, RNN and LSTM
- Assisted Data Scientist to build Auto-encoder Deep Learning model to detect application shutdown
- Participated in Entrepreneurship Program to create a real estate digital startup in Schoolab incubator
- Conducted interviews, conceptualized, and built product prototype to meet customer needs
- Managed end-to-end process including observation, growth hacking, client acquisition and A/B testing
- Audited critical platforms of a telecommunication operator
- Created risk cartographies related to the data center and call center of the operator and followed the risk mitigation plan
- Performed interviews with relevant process owners and executives within Technical Direction
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