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Data with less than a year in Customer Support, skilled in Excel, SQL, Python, and Tableau.
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Motivated Data Analyst with a solid foundation in data science, complemented by recent hands-on training in analytics tools such as Excel, SQL, Tableau and Python. Utilized a career break to upskill and build strong analytical capabilities. Now seeking to apply these skills to solve business problems and add value to an organization.
RTMNU (Nagpur university)
B.E · Electronics & comm.
August 1, 2018 – June 30, 2018
MH-state board
H.S.C
June 1, 2014 – May 31, 2014
MH-State board
S.S.C
June 1, 2012 – May 31, 2012
Corplegal business solution's pvt ltd
Customer Support Executive
January 1, 2026 – Present
India
Finding Business Insight from Employee Resignations
January 1, 2026 – June 30, 2026
Analyzed employee attrition dataset using Python, Excel, and Tableau to identify key factors driving employee resignation. Performed data cleaning, pre-processing and EDA using Python (Pandas, NumPy) and Excel functions. Conducted exploratory data analysis and created interactive dashboards in Tableau to visualize trends in employee turnover. Identified major factors such as salary, job satisfaction, and work experience affecting attrition rates. Delivered actionable insights and recommendations to improve employee retention and support business decision-making.
Exploratory Data Analysis on Omnichannel Platform
January 1, 2026 – June 30, 2026
Conducted EDA on omni-channel data using Python (Pandas, NumPy). Analyzed customer behaviour and sales trends across online and offline channels. Generated insights using data visualization to support business decisions.
Customer Behaviour Analysis with Machine Learning
January 1, 2026 – June 30, 2026
Analyzed customer data to understand purchasing patterns, preferences, and behavioural trends using Python. Performed data cleaning and pre-processing using libraries like Pandas and NumPy to ensure data quality. Conducted Exploratory Data Analysis (EDA) to identify key insights such as customer segmentation, spending habits, and retention patterns. Applied machine learning algorithms (such as clustering and classification models) to segment customers based on behavior and predict future actions. Built models like K-Means Clustering for customer segmentation and Logistic Regression / Decision Trees for behavior prediction. Evaluated model performance using appropriate metrics and improved accuracy through feature selection and tuning. Visualized insights using Matplotlib/Seaborn and created dashboards. Provided actionable business insights to improve customer retention, targeting, and marketing strategies.
Learning Path in Data Science
Board Infinity
October 1, 2022 – Present
Internship done on ARM-8 Raspberry pi module using basics of python programming
Techno vision technologies Pvt. Ltd
May 1, 2018 – Present
Cultural Fit Analysis
The candidate shows a strong drive for learning and career transition into data science, which aligns with a culture of continuous improvement. The project diversity, focusing on customer behavior, omnichannel analysis, and employee attrition, demonstrates a broad interest in applying data science to various business problems. However, the lack of extensive team-based project experience or leadership roles makes it difficult to fully assess cultural fit for a senior position requiring significant collaboration and mentorship.
Soft Skills & Operational Fit
The candidate's profile summary highlights motivation and a proactive approach to upskilling, indicating a positive work attitude. Project descriptions suggest an ability to translate data insights into business recommendations, which is valuable for operational fit. However, the limited professional experience in a data-specific role means direct operational fit in a senior data role is unproven.