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Mayil Huseynov

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Baku, Azerbaijan
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Résumé

Jobs verified_user 0% verified
  • I
    Data Analyst Intern
    Intern Intelligence
    Feb 2025 - Current (1 year 5 months)
    Building predictive analytics models to improve forecasting accuracy, targeting a 10-15% reduction in error rates. Developing interactive Tableau and Power BI dashboards, reducing manual reporting time by ~30% and improving data accessibility. Refined large datasets through data cleaning and transformation, enhancing consistency for decision-making.
  • Saiket Systems
    Business Intelligence Analyst Intern
    Saiket Systems
    Jan 2025 - Feb 2025 (2 months)
  • D
    Robotics Intern
    Device Production Union
    Feb 2023 - Jul 2023 (6 months)
    Contributed to the development and testing of robotic systems with a focus on UAV projects. Optimized control algorithms, cutting response time by 15-20% for smoother operations. Improved prototype stability through testing and troubleshooting, ensuring consistent performance.
  • Algorithmics
    Web Development Intern
    Algorithmics
    Sep 2022 - Jan 2023 (5 months)
    During my internship at Algoritmics in the Web Development program, I gained hands-on experience in building and optimizing web applications. I worked with HTML, CSS, and JavaScript, enhancing both frontend design and functionality. The role allowed me to apply problem-solving skills, collaborate on real-world projects, and improve my understanding of modern web technologies. This experience strengthened my ability to develop interactive and user-friendly web solutions.
Education verified_user 0% verified
  • A
    Master of Robotics and Robot Systems.
    Azerbaijan State Oil and Industry University
    Sep 2023 - Jul 2025 (1 year 11 months)
  • A
    Bachelor of Mechatronics & Robotics Engineering
    Azerbaijan State Oil and Industry University
    Sep 2019 - Jul 2023 (3 years 11 months)
Projects (professional or personal) verified_user 0% verified
  • c
    churn analysis
    Feb 2025 - Mar 2025 (2 months)
    Churn analysis is the process of identifying customers who are likely to stop using a product or service. It involves analyzing customer behavior, transaction history, and engagement patterns to detect potential churn risks. By leveraging data analytics and machine learning, businesses can predict churn and implement retention strategies to reduce customer loss.
  • DataCamp
    Netflix analysis
    DataCamp
    Dec 2024 - Feb 2025 (3 months)
  • R
    Rammdaten
    Dec 2024 - Current (1 year 7 months)
    Rammdaten is an ambitious ongoing project that delves deep into the world of Rammstein, not just as a band but as a cultural phenomenon. It’s a data-driven exploration that aims to collect, analyze, and visualize everything Rammstein-related—lyrics, themes, setlists, fan engagement, and even the evolution of their artistic identity. Think of it as a fusion of web scraping, machine learning, and raw industrial energy, where numbers and metal collide to tell a unique story. This project is more than just data; it’s about decoding the essence of Rammstein—from poetic metaphors to stage pyrotechnics—through the lens of data analytics. Whether it’s uncovering lyrical patterns, tracking fan discussions, or mapping the most explosive moments in l
  • Codecademy
    Exploring Mushrooms
    Codecademy
    Nov 2024 - Jan 2025 (3 months)
    The Exploring Mushrooms project, part of my Codecademy journey, is an analytical dive into the fascinating world of fungi. Through data exploration and visualization, the project examines different mushroom species, their characteristics, and potential edibility. By applying data analysis techniques, it uncovers patterns in mushroom taxonomy, helping to distinguish edible species from toxic ones. This project not only enhances my data skills but also bridges the gap between nature and analytics, turning biological diversity into insightful data-driven narratives.
  • N
    NYC Tree Cencus
    Nov 2024
    Analyzed 500,000+ tree records to uncover correlations between tree distribution and income levels across NYC neighborhoods, providing insights into environmental equity. Visualized key insights using Tableau, creating interactive dashboards to showcase trends and provide actionable insights for urban planning.
  • S
    Spotify Hot 100 Data Analysis
    Sep 2024 - Nov 2024 (3 months)
    In this project, I used MySQL to analyze the Spotify Hot 100 dataset, exploring trends in popular music. I performed data cleaning, aggregation, and querying to extract insights on top artists, genre distributions, and track performance over time. By leveraging SQL functions and joins, I identified patterns in song popularity and listener preferences. This project enhanced my database management and analytical skills, providing a structured approach to music data exploration.