Fișier CV
АА
Data Analyst

Gender Masculin

address Chișinău

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ABOUT ME

Motivated, detail-oriented aspiring data analyst with a strong foundation in SQL, Python, and BI tools. Skilled in data visualization and eager to apply analytical skills in a collaborative environment.

SKILLS

  • MySQL
  • Python (Pandas, NumPy, Matplotlib)
  • Excel
  • Power BI
  • Statistics
  • Jupyter Notebook

HOBBIES & INTERESTS

  • Sports: Actively engage in physical activities to maintain fitness and discipline (volleyball, snowboarding, gym).
  • Reading: Enjoy exploring books on personal development and rarely novels.
  • Healthy Lifestyle: Committed to continuous self-improvement through balanced nutrition, exercise, and mindfulness.

LANGUAGES

  1. Russian - Native language
  2. English - Upper intermediate
  3. Romanian - Upper intermediate

CERTIFICATIONS

  • Cambridge B2
  • SQL (Hackerrank base-mid level certification)
  • Credly (3 certifications from Certiport)

EDUCATION

2013 - 2025 Alexander Pushkin Theoretical Lyceum Chisinau, Moldova
High School Diploma, mediu - 9.15

EXPERIENCE

  • Tech Competitions: FTC/FLL (2018-2025), Tekwill Web Development (2023-2024)
    • Team Lead | Analyst | Programmer
    • Created presentations, reports, and visual materials to showcase team progress and strategic plans.
    • Presented projects to diverse audiences in English, Russian, and Romanian.
    • Analyzed team performance and refined strategies based on error patterns and outcomes.
    • Developed software solutions for robotics and web platforms.
    • Pursued independent learning through free online resources and active collaboration with domain experts to deepen understanding and improve practical skills.

SELF-INITIATED PROJECTS

  • Global Layoffs Analysis Project (2025)

    • Preprocessed and cleaned global layoffs data using MySQL, ensuring consistency and reliability.
    • Conducted exploratory data analysis (EDA) to identify trends across industries and regions.
    • Developed interactive dashboards with Power BI to visualize key insights.
  • Customer Call List Data Cleaning (2025)

    • Fixed common data issues such as duplicates, missing values, and inconsistent formatting in a customer call list dataset.
    • Utilized Python, Pandas, and Jupyter Notebook to preprocess and standardize the data, ensuring readiness for analysis.

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