Microsoft

Started as a Data Scientist and grew to Principal Data Scientist Manager.
My team has supported multiple industries such as retail, gaming, finance, marketing, e-commerce, energy, media, manufacturing, and others. We implement solutions in a wide range of AI areas including recommendation systems, natural language processing, computer vision, time series forecasting, and other machine learning techniques.
Our repository Recommenders ➡️➡️ https://github.com/recommenders-team/recommenders is a 
world reference in recommendation systems. Starred and used by +19k people.

Principal Data Scientist Manager

IE University

I'm helping a new generation of students to understand and apply AI.

Adjunct Professor

Imperial College London

I help the College to define its strategic development, research themes, academic programs, and partnerships with the industry.

Industry Board Member at Dyson School of Design Engineering

samsamia

We developed a SaaS solution to increase fashion e-commerce revenue through visual search. Our technology allowed users to take a picture of a garment they liked, and find the most similar garment within the customer's catalog. I led the engineering and sales team. Among our customers, we had one of the biggest e-commerce in the UK and one of the biggest media companies in Spain.

CEO & Co-Founder

King's College London

Research topics: Learning from Demonstration, Human-Robot Interaction, Markov Chains, and 
Non-linear control.

External Researcher

Universidad Carlos III de Madrid

Research in Machine Learning for robotics: Learning from Demonstration, Computer Vision, kinematic and dynamic control of humanoid robots, and non-linear control. See my publications: ➡️➡️ https://github.com/miguelgfierro/publications

Professor at several Engineering degrees teaching Control Engineering, Industrial Automation, and Industrial Robotics.

Research Assistant at Robotics Lab

Development of algorithms to predict the energy price fluctuation in Spanish electrical market focusing in wind turbines.

Scholarship Researcher in Electric Department

Asociación de Robótica de la Universidad Carlos III

A non-profit student organization at Universidad Carlos III de Madrid. Development of R&D robotics projects including mobile robots, aerial robots (Unmanned Aerial Vehicles UAVs), 3D printers, and small humanoid robots.

President & Co-Founder

I lead the Personalization team at Microsoft working on Reco Systems, NLP, Computer Vision, and other ML solutions.

In addition, I help people understand and apply AI. Whether you want to switch your career to Data Science, land a job in a big tech company, grow your Data Science career, or apply AI to your business, I can help you.

Subscribe to my list ➡️➡️ https://bit.ly/emaillistmiguel ⬅️⬅️

____________________________
Blog: https://bit.ly/miguelgfierro
GitHub: https://github.com/miguelgfierro
Microsoft Recommenders: https://github.com/microsoft/recommenders
Publications and conferences: https://github.com/miguelgfierro/publications

I am at my maximum connections, please follow me and press the bell to stay connected on LinkedIn.

Miguel Fierro

I’ve finished the book: Building AI Agents with LLMs, RAG, and Knowledge Graphs. Really strong book to get a holistic view on how to build agents.

Here are some ideas I found interesting:

𝐇𝐢𝐞𝐫𝐚𝐫𝐜𝐡𝐢𝐜𝐚𝐥 𝐢𝐧𝐝𝐞𝐱𝐢𝐧𝐠:
Problem: If there are too many documents or they are too long, RAG would struggle with precision (chunks are misaligned) or recall (find all relevant chunks).
Solution: We generate a summary of each document and index it with the chunks. At query time, first search over the summaries, and then retrieve the relevant chunks.

𝐒𝐞𝐥𝐟-𝐑𝐀𝐆:
Problem: The query is too complex.
Solution: Use a multi-step process to critique and reflect on the output.

𝐆𝐫𝐚𝐩𝐡𝐑𝐀𝐆:
Problem: Traditional RAG fails to capture relationships and struggles with redundant information.
Solution: Use a Knowledge Graph, composed as tripplets of entity-relation-entity, as a controlled context to increase relevance.

𝐆𝐫𝐚𝐩𝐡 𝐨𝐟 𝐓𝐡𝐨𝐮𝐠𝐡𝐭 (𝐆𝐨𝐓):
Problem: The query is too complex.
Solution: Use multiple reasoning steps in graph form to explore alternative answers and verify the final output.

𝐄𝐱𝐩𝐥𝐚𝐢𝐧𝐚𝐛𝐥𝐞 𝐑𝐞𝐢𝐧𝐟𝐨𝐫𝐜𝐞𝐦𝐞𝐧𝐭 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠 (𝐗𝐑𝐋):
Problem: It’s not easy to understand the agent's behavior in an RL setting.
Solution: Use an LLM as a policy interpreter to explain the agent’s behavior.

Link: https://lnkd.in/dNybQPcj

Window Finance

Building solutions for the Decentralized Finance market.

Applied Data Scientist

Sami

- First Data Scientist at Sami, with the mission of mapping business problems and impactful solutions. 
- Responsible for managing, organizing and developing the Data Science projects, building the full pipelines from data extraction to delivery of results.
- Built models in Growth Marketing (Lead scoring, Social media source conversion forecasting), and other areas (churn prediction, OCR, RFM analysis, etc).
- Some impacts and results: with Lead scoring, version 1 increased conversion in 3x in the first month.
- Stretch-role as a Tech Manager of the Data Science team.
- Mentoring of a Jr Data Scientist.
- Tech stack: Python, SQL, DataBricks, AWS bucket S3, etc.

Senior Data Scientist

Hospital Israelita Albert Einstein

- Project: Model for predicting employee absenteeism caused by mental or behavioral disorders.
- Imbalanced Classification model.
- Tech stack: R, SQL, Docker, Azure, Python, etc.

Data Scientist

Safra

- Projects from multiple areas: Anti-money laundering data analysis, Investigation technology, Juridic, Broker, etc.
- Some solutions: 
  - Risk group identification model (with name similarity analysis)
  - Data correction model (for corrupted files, or typos, using NLP)
  - Scoring system for account opening: backtests
  - Broker alerts with SAS
  - Database creation, with webscraping
- Tech stack: Python, R, SQL, SAS, etc.

Anti-Money Laundering Analyst / Software Engineer

Estalajadeiro

AI Integration Lead

Weduu - Top Line Mining

- Built predictive models for retail 
- Projects: Sales prediction models, recommendation systems, etc.
- Impact: Sales prediction model increased the forecasting performance for most of the products.
- Tech stack: Python, SQL, GCP BigQuery

Data Scientist, Jr

Dom Bosco High School BIlingual Program

Assistant Professor of Mathematics and Physics

Oficina do Aluno

Como professor de Química, Física e Matemática, devia transpor o conhecimento do conteúdo para alunos de Ensino Fundamental e Ensino Médio, aplicando exercícios, aulas, plantões e, por vezes, aulas particulares.

Teacher

Data Scientist and Applied Mathematician | Python, R | Mathematics | Machine Learning | Deep Learning | MLOPs | GCP | Increased lead conversion up to 3x in 1 month

Applied Mathematician | Data Scientist with years of experience in building AI solutions for various areas, such as Startups, Hospitals, Banks.

Experienced with :
- various applications: financial indicators forecasting and estimation, lead conversion prediction, churn analysis, sales prediction, risk group identification, sentiment analysis, etc.
- various Machine Learning and AI fields and areas: Imbalanced Classification, Regression, Deep Learning, Clustering, NLP, Computer Vision, Time Series Forecasting, etc.
- teaching and mentoring: mentoring of Jr Data Scientists, tech talks, teaching Math and Physics in schools, etc.

Example of impact: I've built a lead scoring model that increased a startup conversion rate up to 3x in the first month.

Currently, I'm doing my Masters of Science in Computational and Applied Mathematics, at the Friedrich-Alexander Universität, in Erlangen, Germany.
Also, I hold a Bachelor of Applied Sciences in Applied and Computational Mathematics, with a minor in Statistical Economics. Thesis: "Support Vector Machines: Classification, Kernels, Regression and Optimization" (full remarks).

taplio

The Battle

Miguel Fierro

Pedro Blöß Braga

Followers

Posts

Engagements

Likes

Performance ScoreMiguel Fierro's LinkedIn Performance

Ready to grow your LinkedIn presence?

taplio

The Battle

Miguel Fierro

Pedro Blöß Braga

Followers

Posts

Engagements

Likes

Performance Score.css-goub6s{font-size:var(--chakra-fontSizes-md);font-weight:500;color:var(--chakra-colors-gray-600);display:block;margin-top:var(--chakra-space-1);}Miguel Fierro's LinkedIn Performance

Ready to grow your LinkedIn presence?

Performance ScoreMiguel Fierro's LinkedIn Performance