Resume Data Scientist in Mexico Mexico City – Free Word Template Download with AI

Name: Juan Carlos Mendoza

Email: [email protected] | Phone: +52 55 1234 5678

Location: Mexico City, Mexico | LinkedIn: linkedin.com/in/juanmendoza-data

A dedicated and results-driven Data Scientist with 6+ years of experience in leveraging data to solve complex business challenges. Specialized in predictive modeling, machine learning, and data visualization for industries such as finance, healthcare, and e-commerce. Proven track record of delivering actionable insights that drive strategic decisions. Committed to advancing innovation in Mexico City's dynamic tech ecosystem while supporting local businesses through data-driven solutions.

• Programming Languages: Python, R, SQL, Java
• Data Analysis Tools: Pandas, NumPy, Scikit-learn, TensorFlow
• Data Visualization: Tableau, Power BI, Matplotlib/Seaborn
• Big Data Technologies: Hadoop, Spark
• Cloud Platforms: AWS, Google Cloud
• Languages: Spanish (native), English (fluent)

Lead Data Scientist

Banco Azteca, Mexico City, Mexico | Jan 2021 – Present

• Developed predictive models to identify credit risk patterns among small business clients in Mexico City, improving loan approval accuracy by 25%.
• Collaborated with cross-functional teams to design data pipelines for real-time fraud detection, reducing fraudulent transactions by 18% within six months.
• Created interactive dashboards using Tableau to monitor customer behavior trends across Mexico City’s urban and suburban branches, enabling targeted marketing campaigns.

Data Scientist

Claro México, Mexico City, Mexico | Jun 2018 – Dec 2020

• Utilized machine learning algorithms to analyze telecom customer churn data, resulting in a 15% reduction in attrition through personalized retention strategies.
• Optimized network performance by analyzing large datasets from Mexico City’s 4G and 5G infrastructure, identifying bottlenecks and proposing cost-effective solutions.
• Partnered with the operations team to implement A/B testing frameworks for pricing models, increasing customer acquisition by 12% in key regions of Mexico City.

Junior Data Analyst

Gobierno de la Ciudad de México, Mexico City, Mexico | Mar 2016 – May 2018

• Analyzed public transportation data in Mexico City to improve route efficiency for the Metro and Bus system, reducing average commute times by 7%.
• Developed a dashboard for tracking healthcare service utilization across Mexico City’s public hospitals, enhancing transparency and resource allocation.
• Conducted sentiment analysis on social media data to gauge public opinion on urban development projects in Mexico City, supporting policy decisions.

Bachelor of Science in Computer Science | Universidad Nacional Autónoma de México (UNAM) | Graduated: 2015

Masters in Data Science | Instituto Tecnológico y de Estudios Superiores de Monterrey (ITESM) | Graduated: 2017

• Certified Data Scientist (CDS) – DataCamp | 2020
• Google Cloud Certified – Professional Data Engineer | Google Cloud | 2019
• Advanced Machine Learning with Python – Coursera (University of Michigan) | 2018

Smart Mobility in Mexico City

Developed a machine learning model to predict traffic congestion patterns using GPS data from public and private vehicles. The project was presented at the 2021 Latin American Data Science Conference in Mexico City and received recognition for its potential to reduce urban pollution.

Healthcare Analytics for Public Hospitals

Analyzed electronic health records from three public hospitals in Mexico City to identify early indicators of chronic diseases. The findings were published in the Journal of Health Informatics (2020) and are being used to improve preventive care programs.

E-commerce Customer Segmentation

Created a clustering model using RFM (Recency, Frequency, Monetary) analysis for an e-commerce startup based in Mexico City. The solution helped the company increase customer retention by 20% within three months.

• Spanish: Native
• English: Fluent (TOEFL 105/120)
• Affiliations: Mexican Association of Data Scientists (AMID), IEEE

Available upon request. Contact: [email protected]