JP Aguirre Graf
Verified Expert in Engineering
Data Scientist and Palantir Foundry Developer
Madrid, Spain
Toptal member since December 9, 2024
JP is a senior data scientist and Palantir Foundry expert with extensive experience delivering data-driven solutions in banking, real estate, and supply chain. Skilled in Python, machine learning, ETL processes, SQL, MongoDB, and Tableau, he excels in implementing and managing complex data systems. With expertise in crafting scalable pipelines and dashboards, JP enables seamless integration, analysis, and visualization, empowering organizations to unlock insights and drive measurable results.
Portfolio
Experience
- SQL - 6 years
- ETL - 5 years
- Python - 5 years
- Tableau - 5 years
- Machine Learning - 5 years
- APIs - 5 years
- Large Language Models (LLMs) - 2 years
- Palantir - 1 year
Availability
Preferred Environment
Palantir, Python, Tableau, Machine Learning, SQL, APIs, PostgreSQL, Visual Studio Code (VS Code), Palantir Foundry
The most amazing...
...project I've done is implementing Palantir Foundry. I built the entire business ontology and received excellent feedback from Palantir's development team.
Work Experience
Senior Data Scientist
Crowdfarming
- Implemented Palantir Foundry, transforming data infrastructure and usability. Used Python, machine learning, and generative AI to enhance integration, analytics, and visualization for actionable business insights.
- Implemented BI dashboard structure with Tableau to track metrics like retention and revenue. Aligned insights with strategic goals by collaborating with C-level executives, enabling company-wide, data-driven decision-making.
- Implemented a customer service engine with integrated calls to Salesforce with automation that included large language models (LLMs), which improved the team's efficiency by more than 30%.
- Optimized ETL processes with Node.js to streamline data from MongoDB to PostgreSQL. Created tutorials for non-technical users, simplifying data interpretation and improving accessibility for actionable insights.
Head of Data and Marketplaces
Hamelyn
- Spearheaded digital transformation to optimize shipping and logistics. Developed Python-based tools to improve core processes and enhance operational efficiency across the company.
- Collaborated with the development team to integrate marketplaces, creating a strategic roadmap for future growth and scaling eCommerce operations effectively.
- Implemented productivity tools like Slack and ClickUp, introducing methodologies like Scrum and sprint planning to streamline workflows and improve team efficiency.
Co-founder and CPO
Manax
- Headed the product team and oversaw the entire analytics structure of the company. Managed creative business strategies, fundraising efforts, and human resources and had various critical responsibilities in running and scaling a startup.
- Designed and tested our Apple, Android, and web applications.
- Managed the platform's operations, ensuring the whole end-to-end flow followed the plan.
- Negotiated and secured funding from different investors.
Data Scientist
Servihabitat
- Developed geolocation and data visualization tools using Tableau and Python to analyze and map real estate assets, enhancing insights and decision-making for property management.
- Streamlined data wrangling and validation processes for geolocation projects. Validated coordinates and assessed external provider performance using Python and SQL.
- Automated complex SQL processes to integrate multiple databases into Python, creating monthly reports on document completion, saving significant time and effort.
- Built dashboards in Tableau and Power BI to track department performance and KPIs. Applied machine learning for parameter tuning in a real estate price prediction model, improving portfolio analysis.
Data Analyst
EdgeRed
- Developed new features using R, PostgreSQL, and Python. Automated processes, such as validating data against Google API calls, to improve efficiency and accuracy.
- Standardized and enriched client data using advanced text cleansing techniques, ensuring high-quality datasets for analysis and reporting.
- Conducted trend analysis and data distribution studies and identified critical data issues, enabling better business insights and decision-making.
- Built predictive models for churn likelihood, product purchases, and market pricing, leveraging machine learning to drive strategic insights and forecasting.
Commercial Analyst
Zero Carbon Project
- Conducted in-depth market research on the energy sector and blockchain solutions for carbon offsetting. Analyzed competitor and market performance to identify opportunities and guide future industry development.
- Compiled findings into impactful presentations with graphs and visualizations, enabling directors and stakeholders to make informed business decisions on sales and strategy improvements.
- Identified methods to improve sales and evaluated product performance, providing actionable insights to refine marketing strategies and enhance blockchain-based carbon offset market success.
Experience
Customer Service Engine in Palantir Foundry
I designed robust data transformation workflows and implemented LLM models with automated prompts using Foundry automation flow. I also built user-friendly workshop applications with feedback loops to enhance model performance.
Additionally, I implemented a full API-calling system integrated with webhooks and Salesforce to streamline customer service agent workflows and improve efficiency.
Migrating Whole Company ETL into Palantir Foundry
I established connections with diverse data sources, including MongoDB, Gmail APIs, and PostgreSQL, while coordinating with the IT team to deploy and configure AWS-based agents to support data ingestion into Palantir Foundry. Also, I designed and implemented a robust data ingestion infrastructure to streamline data flows from multiple sources, ensuring high performance and reliability.
I developed a comprehensive data transformation framework within Foundry, leveraging its capabilities to cleanse, standardize, and prepare data for critical use cases. Finally, I built reusable pipelines to support applications and analytical models across various business units, ensuring data readiness for relevant stakeholders.
This migration enabled the organization to modernize its data architecture, improve processing speed, and enhance scalability for future expansion.
Tableau Application with Real Estate Pricing Model
Education
Master's Degree in Data Science for Decision Making
Barcelona School of Economics - Barcelona, Spain
Master's Degree in Data Science
Nuclio Digital School - Barcelona, Spain
Scholarship Program in Economics and Finance
University of Technology Sydney (UTS) - Sydney, Australia
Bachelor's Degree in Economics and Finance
University of Bologna - Bologna, Italy
Skills
Libraries/APIs
Pandas, Amazon API, eBay API, XGBoost, Node.js, NumPy, Google Maps API, Matplotlib, Google APIs
Tools
Tableau, Google Analytics, Slack, Notion, Figma, Plotly, Power BI Desktop
Paradigms
ETL, Agile, App Development
Languages
Python, SQL, R, TypeScript
Platforms
Amazon, Palantir Foundry, Visual Studio Code (VS Code)
Storage
MongoDB, PostgreSQL, Data Integration
Frameworks
Spark
Other
Palantir, Predictive Modeling, Client Relations, Machine Learning, APIs, Large Language Models (LLMs), Google Data Studio, eBay Store, Big Data, Presentations, Analysis, Energy, Green Energy, PowerPoint Design, Market Research & Analysis, Economics, Econometrics, Statistics, Probability Theory, Finance, Mathematical Finance, Hypothesis Testing, Multivariate Calculus, Linear Algebra, Unit Economics, Behavioral Economics, Economic Analysis, Statistical Modeling, Data Science, Artificial Neural Networks (ANN), Artificial Intelligence (AI), EDA, ETL Tools, Multivariate Statistical Modeling, Data Analysis, Calculus, Webhooks, Data Engineering, Data Transformation
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