Building Soda to monitor from data to decision

I love talking about: machine learning, data quality, decision making, post deployment data science, performance estimation, and bunch of other stuff. 

Always open to have a chat 🙂

Hakim Elakhrass

Caylent

• Pioneering Video-LLM solutions for next-gen AI systems.
• Advanced information retrieval architectures.

Senior Machine Learning Engineer

Genesis Consulting Partners, LLC

Working for SKF, one of the largest bearing manufacturer in the world.

• 75% improvement to speed of development in new models from training and deployment model pipeline that I've helped develop in order to have outlier detection features for our condition monitoring tool. 
• 50% increase in tool integration from new data pipelines that I've developed from client APIs in order to increase product fit for our customers.
• 20% decrease in predicted downtime by developing data monitoring tools.

Machine Learning Engineer

Shake

•  Built classification models with Small Language Models (SML) and NLP to compare website similarity for web data aggregation for brand management, participating in a 30% increase in revenue. 
• Fine-tuned SLMs like miniLM and BERT using HuggingFace, PyTorch, and PEFT (LoRA, QLoRA) for web data aggregation, resulting in a 5% accuracy increase.
• Used Vector Databases (ElasticSearch) with embedding models to store and retrieve relevant webpages for small LLMs, resulting in a 10% speed improvement.
• Built their first MLOps pipeline using AWS S3 and AWS SageMaker to use GPUs in our architecture, resulting in 3x times faster inference time.

Data Scientist

BTG Pactual

• Increase in 50% in the development speed for the app Chatbot after I’ve built a Topic Modelling tool that tagged customers topics.
• Estimated increase of 10% in customer call acceptance after I’ve developed a
Recommendation Systems model to predict the best time to call.
• Increase in 100% of directed market campaign for airports marketing using
geospatial analysis.

Oncase

• Worked on the creation of a complete data product that ingested at least 30% faster many different databases, performing full ETL procedure in a parallelized manner using AWS.
• Created data pipelines in order to enrich the data and extract insights for the clients in the context of market research of their products.

Data Engineer

NavalPort

• Pulling data from the database, I modeled their data using Queueing Theory in order to evaluate statistical relevant information and forecast precise navigational and shipping processes.
• Created from scratch data pipelines using Postgres and GIS to extract and explore navigational coordinates in harbors.
• Developed a dashboard to interactively visualize and explore the different outputs from the previous steps.

Universidade Federal de Pernambuco

• I led the construction of the dashboard to carry out interactive reports in addition to visualisation and inspection of fund data, which improved by 50% the decision flow of RECIPREV analysts.
• Through the use of multivariate analysis techniques such as PCA, I proposed new valuable metrics for RECIPREV’s manager, which improved decision making.
• I've also implemented advanced statistical techniques and metrics to analyse and model financial data (GARCH, Markowitz Analysis, etc.), helping to increase profitability and reduce risks in RECIPREV's investments.

• I've researched and reviewed the scientific literature in search of top current statistical models, generating a concrete document that summarises the statistical models in this area. Also, testing in never-before seen scenarios.
• I also developed the beginning of an R package as a collection of codes to advance the research in my specific topic. The package is called distkrige.

Undergraduate Researcher

Passionated about Large Language Models (LLM) and Computer Vision, I seek to understand and disseminate digital intelligence in our societies to answer question and solve problems.

Besides my 5 years of professional experience in Data, I have a BSc in Statistics and I'm currently finishing my Master's Degree in Computer Science with a focus on Artificial Intelligence. I have also a certificate in the Computer Vision Nano-degree program by Udacity.

I'm also happily married, love coffee, video-games and training Brazilian Jiu-Jitsu (BJJ).

Tools and Knowledge:
Machine Learning
Deep Learning
Statistics
MLOps
AWS
Python, R, Julia
PyTorch
LLM
REST API
Data Engineering
Docker
Airflow
Vector Databases

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Hakim Elakhrass

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