Data Analyst - Data Mining & Visualization Specialist

ANKUR PAL

Data Analyst ** yrs

B. Tech SRM University of Lucknow Male

Email: **********@*****.***

Mo: 933-***-****

FIELDS OF INTEREST

Data Modeling, Data Mining, EDA, ETL, Business and Data analysis, Data Science and Visualization. EDUCATION

Examination University Institute Year CGPA/%

Graduation SRM University SRM University of Lucknow 2025 6.31 Diploma SRM University SRM University of Lucknow 2022 6.92 12th

10th

UP

UP

S S A Inter clg Sultanpur

Bariyar Shah inter clg Sultanpur

2020

2018

64%

65%

INDUSTRIAL EXPERIENCE

• Data Analyst Intern Gurugram (Aug’ 25 – Present)

• Collaborated in developing multiple KPI contributed in reducing 17% in Customer Acquisition cost and increasing average revenue per user by 15%.

• Analyzed 20+ Marketing Campaign data to enhance the target customer number by 13% based on geographic region by tracking marketing cost and customer involvement density. RESEARCH & TRANNING EXPERIENCE

Data Analyst Trainee – AnalystixLabs

• Undergoing intensive hands-on training in Data Analytics using Excel, SQL, Python, and Power BI

• Performed data cleaning, preprocessing, and transformation on real-world datasets

• Conducted Exploratory Data Analysis (EDA) to identify trends, patterns, and anomalies

• Used Python (Pandas, NumPy, Matplotlib, Seaborn) for data analysis and visualization

• Wrote SQL queries for data extraction, filtering, aggregation, and reporting

• Designed interactive dashboards in Power BI to track KPIs and business metrics

• Created structured reports and presented insights for decision-making. MAJOR PROJECTS

• Credit Data Analysis Using Python (Dec’ 25)

• A financial health EDA of individuals evaluating factors like annual income, average annual income is 66k USD for good credit score and for poor credit score it is 44k USD.

• Implemented Matplotlib to visualize credit distribution, about 19.9% user have good credit score, 56% user comes under standard credit score and that for bad credit score is 24.1%.

• Fraud Detection in Financial Payment using Python (Jan’ 26)

• Identified over 8,000 fraudulent transactions out of 6.36 million transactions by applying Feature engineering and Data Analysis using numpy and pandas library.

• Performed EDA over destination and origination account behavior of fraudulent transaction and analyzed fingerprint dispersion with transaction amount and time. CERTIFICATION AND PARTICIPATION

• Data science & AI consists of the following courses- 2025

(Python, Java Fundamentals, Design Thinking(vol2), Cloud Application Developer, Data Visualization, Advanced data preparation with IBM SPSS modeler, AI Analys).

• Web Development 2022

• Certified Data Analyst: Microsoft Excel, MS SQL Server and Power BI (Analytixlabs)

• (Project: Retail Analysis, Supply–Chain Data Analysis, Mobil Manufacturer Data Analysis, Hotel Revenue Analysis etc.)

• Python for Data Analysis: Numpy, Pandas, Matplotlib, Seaborn

• (Project: Spotify Recommendation Model, Fraud Detection in Financial Payment, Credit Data Analysis etc.) INTEREST AND HOBBIES

• Technology-related activities.

• Photography.

• Playing outdoor games.

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