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Data Analyst with 2+ years in Data Analytics & Visualization
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Aspiring Data Analyst with a Master's degree in Mathematics and hands-on training in Data Analytics. Proficient in Python, SQL, Power BI, Tableau, Pandas, and data visualization. Seeking opportunities to apply analytical skills to business decision-making.
Vidhyasagar Women's Arts and Science College
M.Sc. Mathematics · Mathematics
August 1, 2017 – June 30, 2019
Vidhyasagar Women's Arts and Science College
B.Sc. Mathematics · Mathematics
August 1, 2014 – June 30, 2017
Archadius Properties
Customer Support & Client Relationship Executive
May 1, 2022 – February 1, 2025
India
Financial Transaction Categorization System
June 1, 2026 – June 1, 2026
Built using Python, Pandas, and SQLite for expense classification and spending analysis.
Sales Analysis System
June 1, 2026 – June 1, 2026
Developed using Python and MySQL for sales reporting and analysis.
Master's in Data Analytics
PUMO Technovation
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's background in mathematics and self-driven projects in data analytics indicate a strong interest and initiative in the field. The transition from a customer support role to data analysis suggests adaptability and a desire for career growth. The personal projects demonstrate a proactive approach to learning and applying new skills, which aligns with a culture of continuous improvement. However, the lack of team-based project experience or professional data analysis roles makes it difficult to fully assess collaboration and broader cultural fit.
Soft Skills & Operational Fit
The candidate's previous role as a Customer Support & Client Relationship Executive suggests experience in client interaction, communication, and problem-solving, which are transferable soft skills for understanding business requirements and presenting analytical findings. However, direct operational experience in a data-driven environment is not evident.