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Alexandre Landi

Alexandre Landi

Lead Data Scientist

IBM | Antibes, Provence-Alpes-Côte d'Azur, France


My Portfolio Highlights

My New Course

Writing Efficient Python Code

Expert data scientist with a passion for solving technical and analytical challenges.

My Work

Take a look at my latest work.


Writing Efficient Python Code


Introduction to LLMs in Python

My Certifications

These are the industry credentials that I’ve earned.

Other Certificates

IBM Data Science Profession Certification - Level 2 Expert

DataCamp Course Completion

Take a look at all the courses I’ve completed on DataCamp.

My Work Experience

Where I've interned and worked during my career.

OpenClassrooms | May 2021 - Present

Data Science Student Mentor


SKEMA Business School | Jan 2020 - Present

Visiting Lecturer


IBM | Sep 2018 - Present

Lead Data Scientist

Agricole Corporate and Investment Banking ● Built email classifier by using NLP methods such as TF-IDF and embedding models and obtaining 88% precision, 70% recall and 78% F1-score on a 10k email dataset for Crédit Agricole Retail Banking ● Achieved 98.8% test set accuracy by using deep learning models such as convolutional neural networks (CNN) on image recognition task within IBM AI Skills Academy Deep Learning Practitioner Pod ● Led team of 5 data engineers and data scientists in a Scaled Agile Framework (SAFe) at Airbus ● Contributed to evidence-based decision-making by providing business intelligence training in Spanish for Viva Aerobus in Mexico for 40+ airline engineer ranging from junior to senior and manager with 4.8/5 customer feedback ● Received 4.9/5 customer feedback on 19-month client assignment at Airbus ● Coached and mentored 7 IBM data scientists and aspiring data scientists across India, Brazil, Morocco and France
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FQT Research | Jun 2016 - Sep 2018

Lead Data Scientist

● Performed data wrangling, exploratory analysis, visualization and ML prediction on 10+ mln data points and 20+ features ● Developed mid-frequency quantitative trading models across asset classes ● Provided direction to build database storing 5 million market updates/day of unfiltered real-time Level I and Level II Eurex data from live feed by connecting to its API (1.5 million Bund + 3.5 million EuroSTOXX) ● Led 3-people team and coordinate software design, implementation and testing ● Developed rigorous research framework and protocol to build and validate quantitative models

Eonos Investment Technologies | May 2014 - May 2016

Quantitative Researcher

● Coded statistical moment functions in Common Lisp which ran 5 times faster than R equivalent library by implementing ideas found in relevant academic papers ● First researcher to bring knowledge of Common Lisp programming language to the company by getting to it from scratch and delivering internal presentations on it ● Obtained 14k EUR/year scholarship + additional government funding from Ministry of Research for Ph.D. thesis “Common Lisp for Statistics: an alternative to R”

LRDE - Laboratoire de Recherche et Developpement d'EPITA | Jan 2015 - Mar 2016

Research Assistant

● Hired as first laboratory member with no prior formal scientific background as result of showing sufficient understanding of Ph.D. research topic as well as outstanding motivation ● Worked on Ph.D. thesis “Common Lisp for Statistics: an alternative to R” in partnership with Eonos Investment Technologies, enrolled at Université Pierre et Marie Curie (Paris VI) ● Thesis topic: "Dynamic languages have gained considerable popularity for data analysis and scientific computing purposes. They tend to be considered very productive, but often offer modest performance. R makes no exception. On the other hand, languages like C or Fortran provide high performance but high cost in development time. The purpose of our research is to explore better alternatives to R in terms of both performance and expressivity. We started considering Common Lisp as a candidate for such purposes but we are open to explore further alternatives."

Kearney | Aug 2012 - Jan 2013

Junior Research Analyst

needs. ● Gathered the necessary raw information using a broad spectrum of sources and organized, analyzed, and synthesized the findings into targeted, firm- formatted end products. ● Worked with sources such as Bloomberg, Capital IQ, Factiva, Dealogic, ISI, ProQuest, Profound, EBSCO, APQC, etc.

My Education

Take a look at my formal education

Master of Science - MS, Computer ScienceGeorgia Institute of Technology | 2025
Master of Science - MS, Financial Markets and InvestmentsSKEMA Business School | 2014
Bachelor's Degree, Humanities/Humanistic StudiesUniversità Cattolica del Sacro Cuore | 2012

About Me

Alexandre Landi

I am an IBM-certified Expert Data Scientist with a passion for leading and empowering teams in solving technical and analytical challenges.

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