Hi,
my name is
my name is
- MSc in Data Science
- 5+ years of experience in
- Machine Learning
- Data Engineering
- Artificial Intelligence
Alberto Avila-Garcia,
and I build data/ML solutions
and I build data/ML solutions
Profile
I have 5+ years of industry experience in Python, data science, data engineering and machine learning and a Masters degree in Data Science by the University of Calgary. I have developed fraud detection algorithms, behaviour prediction projects, end-to-end data engineering pipelines among other.
I love what I do, and I am passionate about it.
Let's build something together!
My skills
Professional experience
Data/ML Engineer @ ISI
May 2023 - October 2023
- Responsible for design, orchestration and launch of data flows in end-to-end deployments for marketing, sales and several areas.
- Built data pipelines on AWS using Lambda, Athena, RDS and ECR resulting in <5s data ingestion.
- Completed Facebook marketing data ingestion pipeline to summarize tens of accounts, campaigns, and ads.
Technologies: Python, SQL, AWS lambda AWS Athena, AWS RDS, Docker, Kubernetes.
- Built data pipelines on AWS using Lambda, Athena, RDS and ECR resulting in <5s data ingestion.
- Completed Facebook marketing data ingestion pipeline to summarize tens of accounts, campaigns, and ads.
Technologies: Python, SQL, AWS lambda AWS Athena, AWS RDS, Docker, Kubernetes.
Data/ML Engineer @ Intelius AI
March 2022 - December 2022
- Responsible for design, orchestration and launch of data flows in end-to-end deployments for stock and crypto markets.
- Designed real-time crypto pipeline achieving 5 seconds of end-to-end execution time.
- Developed reinforcement learning algorithm to predict price direction surpassing 82% accuracy.
Some of the technologies I used are Apache Airflow, Kafka, Prefect, Kubernetes, Dockers, Python, Keras, Redis, MySQL and GCP.
Technologies: Python, SQL, Kafka, GCP, TensorFlow, Prefect orchestrator, Kubernetes.
- Designed real-time crypto pipeline achieving 5 seconds of end-to-end execution time.
- Developed reinforcement learning algorithm to predict price direction surpassing 82% accuracy.
Some of the technologies I used are Apache Airflow, Kafka, Prefect, Kubernetes, Dockers, Python, Keras, Redis, MySQL and GCP.
Technologies: Python, SQL, Kafka, GCP, TensorFlow, Prefect orchestrator, Kubernetes.
Big Data Engineer @ Expedia Group
Dec 2020 – Aug 2021
- Boosted user engagement in 18% by designing cluster and segmentation model in Scikit-learn.
- Increased data availability by enhancing Spark code in Airflow pipelines and boosted data's up time by 25%.
Technologies: SQL, Hadoop, Airflow, Python, bash scripting, AWS.
- Increased data availability by enhancing Spark code in Airflow pipelines and boosted data's up time by 25%.
Technologies: SQL, Hadoop, Airflow, Python, bash scripting, AWS.
Data Scientist @ Banco del Credito del Peru
Mar 2020 - Dec 2020
- Developed fraud detection ML algorithm (comprised of data engineering, cluster analysis, feature selection, SVM outlier detection) to predict future occurrences in place and time predicting with 96% accuracy.
- Formulated scoring system to focus resources resolving top 10% incidents that caused 92% money loss.
Technologies: Python, Sci-Kit learn, Pandas, Keras and Numpy.
- Formulated scoring system to focus resources resolving top 10% incidents that caused 92% money loss.
Technologies: Python, Sci-Kit learn, Pandas, Keras and Numpy.
Data Scientist @ Citi Group
Jul 2018 – Mar 2020
- Designed ML pipeline for credit card usage classification to expedite understanding of clients achieving 85% increase in client categorization accuracy.
- Implemented credit scoring system to measure credit behaviour and offer the best possible financial product to clients yielding 2x faster computations for 20M+ people in business portfolio.
Technologies: SQL, Python, PySpark, Sci-Kit Learn, Tensorflow, Hadoop.
- Implemented credit scoring system to measure credit behaviour and offer the best possible financial product to clients yielding 2x faster computations for 20M+ people in business portfolio.
Technologies: SQL, Python, PySpark, Sci-Kit Learn, Tensorflow, Hadoop.
FCA Engineer @ Ford Motor Company
Aug 2017 - Jul 2018
- Built and implemented automated data processing tool to generate reports and validate parts for manufacturing, engineering and finance teams.
- Decreased validation time from hours to minutes.
Technologies: VBA programming, Excel
- Decreased validation time from hours to minutes.
Technologies: VBA programming, Excel
Stuff I have built
The Silent Cartographer
AWS-powered ETL
Crypto Visualizer
Anomaly Detection in ATMs
DoggoNet
Let's connect
Whether you have a question or just want to say hi,
I would love to hear from you!
Feel free to book a call with me by clicking the calendar icon below,
send an email or connect via LinkedIn or GitHub.
