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Hi, I’m Diego Ortiz Puente, a data scientist with a finance background who turns complex data into actionable business insights. I have led data-driven initiatives at NielsenIQ, modernizing estimation processes through web scraping and statistical modeling, which boosted accuracy and efficiency. I’m proficient in Python, SQL, Power BI, and data storytelling. Currently relocating to Melbourne in February 2026 and pursuing a Bachelor’s in Mathematics & Statistics at the University of Melbourne, I’m open to part-time analytics engagements while continuing my studies.…Hi, I’m Diego Ortiz Puente, a data scientist with a finance background who turns complex data into actionable business insights. I have led data-driven initiatives at NielsenIQ, modernizing estimation processes through web scraping and statistical modeling, which boosted accuracy and efficiency. I’m proficient in Python, SQL, Power BI, and data storytelling. Currently relocating to Melbourne in February 2026 and pursuing a Bachelor’s in Mathematics & Statistics at the University of Melbourne, I’m open to part-time analytics engagements while continuing my studies.

Diego Ortiz Puente

Data Scientist, Data Analyst, AI Engineer, +2

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Hi, I’m Diego Ortiz Puente, a data scientist with a finance background who turns complex data into actionable business insights. I have led data-driven initiatives at NielsenIQ, modernizing estimation processes through web scraping and statistical modeling, which boosted accuracy and efficiency. I’m proficient in Python, SQL, Power BI, and data storytelling. Currently relocating to Melbourne in February 2026 and pursuing a Bachelor’s in Mathematics & Statistics at the University of Melbourne, I’m open to part-time analytics engagements while continuing my studies.…Hi, I’m Diego Ortiz Puente, a data scientist with a finance background who turns complex data into actionable business insights. I have led data-driven initiatives at NielsenIQ, modernizing estimation processes through web scraping and statistical modeling, which boosted accuracy and efficiency. I’m proficient in Python, SQL, Power BI, and data storytelling. Currently relocating to Melbourne in February 2026 and pursuing a Bachelor’s in Mathematics & Statistics at the University of Melbourne, I’m open to part-time analytics engagements while continuing my studies.

Available to hire

Hi, I’m Diego Ortiz Puente, a data scientist with a finance background who turns complex data into actionable business insights. I have led data-driven initiatives at NielsenIQ, modernizing estimation processes through web scraping and statistical modeling, which boosted accuracy and efficiency. I’m proficient in Python, SQL, Power BI, and data storytelling.

Currently relocating to Melbourne in February 2026 and pursuing a Bachelor’s in Mathematics & Statistics at the University of Melbourne, I’m open to part-time analytics engagements while continuing my studies.

Skills

Experience Level

Expert

Expert

Expert

Expert

Language

English

Fluent

Work Experience

Junior Data Scientist at NielsenIQ

March 1, 2025 - Present

Updated Argentina’s store universe estimation by replacing legacy databases with automated data pipelines in Python, improving accuracy and update speed of key indexes. Recalculated auxiliary variables to improve precision and optimize sampling metrics. Designed validation templates for Share of Wallet extractions via SQL queries, streamlining workflows and uncovering key optimization opportunities. Consolidated and standardized datasets across major services (Retail Measurement Service, Industry Coverage Matrix), ensuring high-quality data delivery for decision-making. Conducted market share and distribution analysis for 50+ manufacturers across 90+ FMCG categories.

Procurement Intern at Laboratorios Carnot

October 1, 2024 - March 1, 2025

Automated key processes with Python and integrated KPI monitoring in Power BI and SAP, reducing workload by 80%.

Internal Auditor at Enel Green Power North America

June 1, 2023 - December 1, 2023

Identified key risks through data analysis and proposed solutions that reduced liabilities by $400k USD.