Alex Molas

Experience

Lead ML initiatives for the search team focusing on matching, ranking, and software best practices. Used Solr as the search engine.
Trained a ranker ML model and deployed it to Solr, improving search-to-transaction ratio by +1.5%, adding 600K€ annually.
Trained and deployed a BERT model for a query classification service. Improved the search-to-transaction ratio by 1%, adding 400K€ annually.
Trained a PoC ranker model that used real-time features such as item popularity. Improved offline NDCG metrics by +10%.
Developed PoC solutions for query understanding (intent extraction from queries and structured attribute extraction from descriptions) using LLMs.
Refactored ETLs from manually executed notebooks to Spark jobs. Reduced execution time from days to hours, improving developer experience and scalability.
Organized events to increase machine learning visibility: internal hackathons, Meetups, and conferences.

Deployed a service that improved ETA accuracy by +30% using a deep learning model. Achieved a +28% improvement in cold-start locations.
Designed and developed pipelines to automatically train, evaluate, and deploy ETA models.
Built a distributed pipeline to process daily all the events dumped from Kafka to S3, allowing DS to analyze and train models on it.
Designed an experimental dispatcher engine to solve the assignment problem using Python and OR-Tools.
Planned a PoC using LightGBM to estimate the probability of a courier accepting a specific delivery.
Mentored a senior software engineer who wanted to specialize in machine learning and data science

Started a recommender system based on implicit user feedback to recommend similar profiles to users.
Implemented a backend ML solution to classify clothes based on images and descriptions.

Implemented an ML model to forecast clearance sales. Launched a pricing engine on top of the forecast model.

Developed tools for monitoring and optimizing SEM campaigns using Google AdWords and Python.

www.alexmolas.com: I've been maintaining since 2020 a blog about data science. Over 70k visits during 2023.
Since 2022 I've been teaching the Data Engineering subject in the Master's on Big Data and Analytics at EAE.
1st place Novartis Datathon (2021) and Aily Datathon (2022). Participated in a dozen other datathons.
Lightning talk in the BCN PyDay 2022 about how to beat your friends in fantasy football using scrapping and operations research.

"Static Typing in Python". Workshop in PyDay 2024. Repo with code and slides (2024)
"A search engine in 80 lines of Python". Blog (2024).
"How to beat your friends in fantasy football", PyDay ES 2022. Blog and Slides (2022).
"Field theory for recurrent mobility". Nature Communications 10, 3895 (2019).
"Streak Camera Calibration Using RF Switches". 5th IBIC, MOPG55 (2017).
"Social network analysis of communities in literature" poster. Won the IFISC Best Poster Award.

Got an IFISC Mobility Scholarship that covered my fees and year expenses during my studies.
Won the best poster award and presented the results at the local radio station.
Master thesis using field theory and data analysis to study recurrent mobility. Results were published in Nature Communications.

Worked as an assistant professor in the subject of numerical methods.
Internship at the ALBA synchrotron. Results were published at the 5th IBIC conference.
Summer internship at IFAE. Worked on Yang-Mills theory simulations.
Received a scholarship from the Spanish government every year for my academic achievements.