Adel Basli's Resume

Profile

I am a highly motivated and results-oriented data science leader with over 11 years of experience in leveraging machine learning and AI to drive business value. Throughout my career, I have focused on applying AI to improve health, wellness, and nutrition . Some of my significant accomplishments include:

Led automation initiatives that improved efficiency and reduced costs by millions of dollars
Developed and deployed innovative machine learning models that increased revenue, reduced risks, and improved decision-making processes
Built and managed high-performing data science teams, fostering a collaborative and agile environment
Possess a strong educational background in engineering and data science, with a Master's degree from Ecole Centrale Paris and experience at MIT Sloan School of Management

In my current role as Team Lead Data Science & AI at Label Insight, I am responsible for leading a team of data scientists in developing and deploying cutting-edge AI solutions to support dietitians.

Areas of Expertise

Agile Project Management
Data Pipelines
Team Leadership
Deep Learning
Full-Stack Development
CI/CD Pipelines

Professional Experience

Team Lead Data Science & AI, (Label Insight) Paris, FranceNutrition

10/2023 - present

Led automation initiatives for 27,000+ product attributes and taxonomies maintenance, collaborating with dietitians, food scientists, and chemists.
Managed cross-functional partnerships between data science teams and subject-matter experts to optimize data foundation systems.
Led data science initiatives for Label Insight driving strategic projects that propelled data-based decision-making processes, achieving a 35% increase in operational efficiency, reducing data processing costs by 20%, and enhancing predictive analytics accuracy by 25%.
Managed design and implementation of data science and deep learning systems, achieving a 35% improvement in system efficiency and a 20% increase in data accuracy.
Collaborated with engineers and product managers to establish data science goals and practices for a 5-person team, increasing team productivity by 25% and reducing delivery times by 15%.
Led strategic code implementation for 50+ daily deployments, achieving a 30% increase in deployment success rate.
Managed financial operations (FinOps) for cost-effective data science solutions, reducing operational costs by 20% while maintaining performance. Additionally, prioritized data initiatives based on ROI and alignment with business goals.
Developed and implemented an advanced outlier correction model utilizing GenAI, LangChain, and RAG technologies, significantly enhancing data quality and reducing errors by 50%. Additionally, integrated Elasticsearch to improve data accuracy, reducing manual decision-making by 27%.

Lead Data Scientist, (Label Insight) Chicago, USANutrition

01/2023 - 10/2023

Led Scrum ceremonies, promoting Agile methodologies.
Developed GenAI-based classifier with LLM, saving $3MM/yr in data transformation costs.
Deployed scalable real-time data system on AWS, reducing processing time by 40% and ensuring fault tolerance.
Used Amazon Personalize for real-time recommendations, increasing CTR by 30% and AOV by 25%.
Implemented innovative data science solutions such as RAG and prompt engineering within BAU processes, leveraging generative AI technologies to optimize operations time and reduce delayed deliveries by 40%, thereby driving strategic advancements.

Senior Machine Learning Engineer - R&D Lead, (Nielsen IQ) Chicago, USANutritionMarket Research

01/2021 - 12/2022

Led a team of 6 in supporting complex machine learning application rollout across 9 servers.
Implemented CI/CD in cloud migration, improving Mean Time to Repair (MTTR) by 80%.
Directed research on Transformer and LSTM algorithms, achieving 5% accuracy gain.
Optimized scalable NLP system with transformer architectures, improving language generation by 10%.
Built stacking ensemble combining machine learning and deep learning algorithms, improving accuracy by 14% and automating predictive tool deployment.

Data Operations Transformation Lead, (The Nielsen Company) Chicago, USANutritionMarket Research

01/2019 - 12/2020

Leveraged machine learning to optimize operations and drive innovation across a portfolio of 8 global business units.
Achieved $5 million cost reduction by replacing classifiers with Neural Networks, CNNs, and NLP.
Automated custom reports using Python, SQL, and Hive, reducing SLA by two days.
Developed autoML platform, generating $12 million in incremental revenue and cost savings.
Led research, development, and deployment efforts, building, enhancing, and pushing a portfolio of 60,000+ models to production.

Senior Data Scientist, (The Nielsen Company) Paris, FranceFMCGMarket Research

01/2016 - 12/2018

Developed machine learning models for customer segmentation, increasing customer retention by 8%.
Used MapReduce for Big Data processing and ETL, reducing M&A integration timeline by six months.
Deployed unsupervised item coding system using fuzzy matching, generating $400,000 in additional revenue.
Built production server for intensive algorithms, reducing computational costs by 30%.
Implemented web scraping and email content identification, reducing manual work by 75%.

Data Scientist, (Air Liquide) Newark, USAIndustryHealthcare

03/2014 - 12/2015

Developed predictive tools for liquid gas demand forecasting, reducing inventory costs by 15%.
Created process control tool to ensure membrane fiber quality, saving $500,000 annually and increasing efficiency by 18%.
Used stochastic modeling to optimize risk/return ratios, increasing revenue by 10% and reducing potential losses by 8%.

Actuary Intern, (AXA France) Paris, FranceInsurance

06/2013 - 12/2013

Led and executed key internal research projects, resulting in the development and deployment of a new density function.
Enhanced financial modeling accuracy, contributing to an improvement in regulatory reporting standards.
Collaborated with cross-functional teams to integrate data-driven methodologies, supporting 3 major regulatory initiatives.

Business Controller Intern, (Airbus) Munich, GermanyAerospace

09/2011 - 08/2012

Assisted in establishing target settings for key financial metrics over a five-year period.
Conducted comprehensive benchmarking and scenario analyses to evaluate internal financial performance, identifying variances between forecasts and actual results.
Leveraged VBA and FACTS+ to automate processes, enhance data accuracy, and streamline financial reporting.

Online Courses & Certifications

Diploma in Human Nutrition (Score: 93/100) (Nov. 2024) - Alison
MLS-C01 (AWS Certified Machine Learning - Specialty - Score: 910/1000) (Nov. 2023) - AWS
SAA-C03 (AWS Solutions Architect Associate) (Oct. 2023) - AWS
CLF-C01 (AWS Certified Cloud Practitioner) (Aug. 2023) - AWS
CAPM (Certified Associate in Project Management) (Jan. 2022) - PMI
AZ-900 (Microsoft Azure Fundamentals) (Dec. 2021) - Microsoft

Education

MSc in Engineering, Ingénieur Centralien

Ecole Centrale Paris, Paris, France (2009-2013)

Prestigious and selective Grandes Ecoles, with a primary focus on Computer Science, Quantitative Research and Applied Mathematics.

Relevant Courses: Data Mining & Machine Learning, Computer Vision & Image Recognition, Risk & Uncertainty Modeling, Optimization, Time Series Analysis & Forecasting.

Visiting Student

MIT SLOAN School of Management, Cambridge, USA (2011)

Research: How different types of side knowledge can reduce the hypothesis space and improve the generalization performance of supervised learning algorithms.

Courses: Statistical Reasoning and Data Modeling, Statistical Learning and Data Mining, Statistical Inference in High-Dimensional Settings, Artificial Intelligence.

Classes Prépa

Lycée Kleber, Strasbourg, France (2006-2009)

Specialization: Intensive preparation in Mathematics, Physics, and Engineering Sciences to qualify for entry into prestigious Grandes Écoles

Courses: Advanced Mathematics, Theoretical Physics, Engineering Sciences, Computer Science, Philosophy, Modern Languages.

Academic Research & Open Source Contribution

Hackathon Winner [1], French Government, France (2024) - Food Data Hackathon
Trainer, EUROSAE, France (2024) - The renewal of artificial intelligence
AI Contributor, Open Food Facts, Remote (2018 - Now) - Collaborative food products database
Author, AlChE, USA (2015) - Batch Process Monitoring By Dynamic Time Warping and K-means Clustering.
Contributor, MIT, USA (2011) - Generalization Bounds for Learning with Linear, Polygonal, Quadratic and Conic Side Knowledge.

Skills

Data Science: Machine Learning, Statistical Analysis, Predictive Modeling, Hypothesis Testing
Programming Languages: Python, R, SQL
Machine Learning Libraries: Scikit-learn, TensorFlow, PyTorch, Keras
Cloud Computing: AWS, Microsoft Azure, Google Cloud Platform (GCP)
Data Visualization Tools: Matplotlib, Seaborn, Tableau, Microsoft Power BI, Excel
Big Data Technologies: Hadoop, Apache Spark, Hive, Pig
Software and Tools: Jupyter Notebook, RStudio, Anaconda, Git, Jira, CircleCI
Project Management: Agile Methodologies, Scrum, Kanban, Jira, Microsoft Project
Soft Skills: Presentation, Planning, Organization, Creative Problem-Solving, Teamwork, Active Listening, Adaptability, Analytical Thinking

Languages

French [Native]
English [Fluent]
German [Intermediate] - Learning

Countries I Lived In

"Once you stop learning, you start dying."

- Albert Einstein

Adel Basli