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Senior AI/ML Scientist & Engineer | Ex-McKinsey
Senior ML Scientist & Engineer with 12+ years of experience leading and scaling high-performing teams to tackle complex business challenges with Analytics, Machine Learning, GenAI & LLMs, and Big Data solutions. Highly skilled programmer with proficiency in Python, Tensorflow & Pytorch, Scala, Java, Spark, Databricks, Amazon AWS. My expertise: • Deep Learning, Machine Learning, GenAI: expert in building and deploying deep learning and machine learning models using: TensorFlow, Keras, Scikit and Spark. Strong experience in distributed training on GPUs, and in deploying online fast inference models using TensorFlow Serving. • Big Data Infrastructure Design: strong understanding of designing and implementing Machine Learning and Big Data Analytics architectures and pipelines, ensuring scalability and efficiency. • Technical leadership: coaching and leading data science teams in delivering impactful ML/AI projects. • Business Impact: tangible business results through data science solutions, in areas like revenue generation, cost reduction, and risk management.
MIT Sloan School of Management
Executive Education Program in Strategy and Innovation
January 1, 2015 – January 1, 2015
University of Illinois Chicago
Master of Science (M.Sc.), Computer Science
January 1, 2011 – January 1, 2012
Politecnico di Milano
Master of Science (M.Sc.), Computer Engineering
January 1, 2010 – January 1, 2012
Politecnico di Milano
Bachelor of Science (B.Sc.), Computer Engineering
January 1, 2007 – January 1, 2010
Expedia Group
Senior Machine Learning Scientist
May 1, 2017 – Present
Geneva, Geneva, Switzerland
McKinsey & Company
Lead Data Scientist
April 1, 2016 – April 1, 2017
Milan, Lombardy, Italy
Business Integration Partners
Lead Data Scientist
March 1, 2013 – April 1, 2016
Milan, Lombardy, Italy
University of Illinois at Chicago
Researcher @ Electronic Visualization Laboratory (EVL)
June 1, 2012 – January 1, 2013
University of Illinois at Chicago, Greater Chicago Area
Introduction to Data Science, Building Recommender Systems
Cloudera
June 24, 2026 – Present
Computing for Data Analysis
Coursera
June 24, 2026 – Present
Developing Innovative Ideas for New Companies
Coursera
June 24, 2026 – Present
Google Analytics IQ
June 24, 2026 – Present
MIT - Tackling the Challenges of Big Data
MIT Professional Education
June 24, 2026 – Present
Software as a Service
edX
June 24, 2026 – Present
E20-007 - Data Science Associate
Dell EMC
June 24, 2026 – Present
Executive Certificate in Strategy and Innovation
MIT Sloan Executive Education
June 24, 2026 – Present
TOEFL iBT English Exam
ETS
June 24, 2026 – Present
Financial Engineering and Risk Management Part I
Coursera
June 24, 2026 – Present
Machine Learning
Coursera
June 24, 2026 – Present
Neural Networks and Deep Learning
Coursera
June 24, 2026 – Present
Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization
Coursera
June 24, 2026 – Present
Structuring Machine Learning Projects
Coursera
June 24, 2026 – Present
Convolutional Neural Networks
Coursera
June 24, 2026 – Present
Sequence Models
Coursera
June 24, 2026 – Present
Deep Learning Specialization
Coursera
June 24, 2026 – Present
Cultural Fit Analysis
The candidate's diverse experience across e-commerce, consulting, and research, coupled with a strong academic background and numerous certifications, suggests a proactive, growth-oriented individual. The focus on delivering measurable business impact aligns with performance-driven cultures. The breadth of projects, from optimizing hotel search to predicting loan defaults and churn, demonstrates adaptability and a wide range of interests, which could contribute positively to a dynamic team environment. However, the target role is 'Data Analyst' while the experience is heavily skewed towards 'Machine Learning Scientist' and 'Data Scientist', which might indicate a potential mismatch in day-to-day responsibilities and expectations, requiring clarification.
Soft Skills & Operational Fit
The candidate's experience as a Lead Data Scientist and Senior Machine Learning Scientist, including co-founding a practice and advising M.Sc. theses, suggests strong leadership, mentorship, and project management capabilities. The consulting background implies excellent communication, problem-solving, and stakeholder management skills. The ability to win a global hackathon indicates innovation and teamwork.