Felipe A.
Data Scientist
His technical proficiency includes working with advanced Data Science and ML tools such as Snowflake, dbt, Airflow, and MLflow. A career highlight was his role at Cambridge University, where he developed and taught an advanced online data science course, showcasing both his subject-matter expertise and ability to simplify complex topics. Additionally, at Outra, he played a key role in securing a multi-million-dollar contract with Zoopla.
Felipe’s unique blend of deep technical knowledge and strong communication skills positions him as a standout professional in the field of Data Science.
Main expertise
Pytest2 years
AWS3 years
Bash4 years
Data Science6 yearsExperience6
Lead Data Scientist
- Worked at Rylee, an e-commerce platform that provided customers with product insights and market analysis to improve strategies on Bol.com and Amazon.
- Earned Databricks certification in Generative AI, demonstrating expertise with RAG and Agent models.
- Developed a large-scale sales forecasting model using Rylee’s internal data and scraped data from Bol.com to predict product sales and identify bestsellers.
- Built an API with Flask and AWS Lambda to handle product queries, delivering insights and sales forecasts.
- Designed and implemented ETL pipelines using dbt, Airflow, and Spark to automate feature engineering, including an asynchronous solution for efficient data retrieval from the Bol.com API while respecting rate limits and parallelizing at scale; also automated data reconciliation across multiple sellers.
- Applied PyTorch and Spark to optimize high-performance machine learning models.
MySQLAWS
Databricks
Apache Spark
Django
Lead Data Scientist
- Worked at Homemove, a comprehensive platform offering moving-related services, including surveys, removals, and mortgages, integrated within a single app.
- Developed an LLM-powered negotiation tool that allowed users to obtain quotes and negotiate prices via an AI chatbot, automatically added customers to the CRM, and alerted the sales team upon successful negotiation, using OpenAI Assistant and GPT models.
- Led a scalable data transformation initiative, leveraging Snowflake for cloud data warehousing and Sigma for BI and visualization.
- Designed and implemented ETL pipelines from scratch using Snowflake, Python, SQL, dbt, and Airflow to automate data ingestion and transformation.
- Built a predictive modeling solution to reduce marketing costs and improve targeting by identifying high-potential home movers.
- Applied PyTorch and Snowpark for advanced machine learning to optimize high-performance models.
- Delivered a predictive model that was planned for use in attracting investment during Homemove's Series A funding.
MySQLAWS
ElasticSearchDatabricksApache SparkData Science Instructor and Course Developer
- Worked as a Data Science specialist at FourthRev, creating and teaching an advanced online data science course for Cambridge University students.
- Developed and delivered a comprehensive curriculum covering Neural Networks, NLP for AI, Unsupervised Learning, and advanced Decision Tree algorithms including XGBoost.
- Applied hands-on machine learning implementation from scratch and employed innovative teaching methods to enhance student engagement and learning outcomes.
- Demonstrated deep technical expertise in data science and machine learning, earning recognition from academic peers for effective teaching and curriculum design.
Data Science
NumPy
XGBoost
Pandas
Scikit-learn
Senior Data Scientist
- Worked at Outra, a data-driven property insight company, specializing in delivering household-level data to optimize client services.
- Migrated the platform from Dataiku to a custom in-house Intelligence Fabric using MLflow, Airflow, Snowflake, GitHub Actions, AWS, and DBT for data engineering.
- Developed two major predictive models forecasting household listing and sale/rent timelines, enabling a multi-million-pound partnership with Zoopla.
- Applied LLMs for code documentation, coding assistance, and interactive chatbots for dashboards and customer-facing data.
- Built ETL/ELT pipelines to transform raw data and prepare it for modeling.
- Created visualizations and maps using KeplerGI, Seaborn, and Dataiku to help non-technical users interpret complex data.
AWSApache SparkDjango
Flask
Python
Senior Data Scientist
- Worked at Belmont Green, a specialist mortgage lending company turned bank, providing financial and mortgage solutions to financially affected customers.
- Created a conversion model using survival analysis techniques and managed the project from inception to production.
- Built machine learning algorithms and statistical models for time series data, focusing on retention, lifetime value, and expected loss models.
- Owned projects end-to-end, ensuring proofs of concept were implemented and deployed successfully in production.
- Implemented machine learning algorithms for cashflow, early redemption, default, pre-payment, and conversion models using Python and R.
- Applied clustering and segmentation techniques to analyze product usage and customer behavior for marketing and strategic purposes.
Data ScienceNumPyXGBoost
KerasPandasData Scientist
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Boster.Ai is a company dedicated to create No-code bots for data retrieval, monitoring and automation. Originally, they started as an IT consultancy company, creating personalized solutions to small and mid-size companies to harvest the power of Machine Learning
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Felipe worked performing data exploration, analysis, and building Machine Learning algorithms and statistical models for several start-ups/mid-size companies in the UK and USA.
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He built and diagnostic Neural Networks models for forecasting key performance indicators using Python, TensorFlow, and Keras.
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Worked in e-commerce businesses solving customer behaviour problems such as lifetime value, clustering of customers, etc.
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Performed ethical web scraping using Python with scraPy, RoboBrowser, and BeautifulSoup to obtain data for various analyses.
Data Science
TensorFlowNumPyKerasPandasEngineering excellence
All Data Scientists who have applied to Proxify are scored from 0 to 300 on engineering excellence, one of the five parameters we evaluate. This score reflects engineering excellence only, based on interviews, take-home assignments, live coding sessions, and/or on-the-job performance reviews. The curve shows how all evaluated Data Scientists are distributed across that range, where our acceptance threshold for this parameter sits, and where Felipe stands.
Score 181 · Top 14% of engineers
Certificates 1
Issued Jan 2025 - Expires Jan 2027
Credential ID 129682840
DatabricksIssued Jan 2025 - Expires Jan 2027
Credential ID 129682840
DatabricksEducation
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