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TIRUMADI JANAKIRAM

Data Analyst • Andhra Pradesh, India • j*****************@gmail.com • +91*******780 • linkedin.com/••••• • drivetube.ai/•••••

Career Objective

Data Analyst with 0.5 years of experience applying Python, SQL and Power BI to analyze customer datasets, build dashboards and deliver actionable business insights. Experienced in cleaning and transforming 10,000+ customer records, engineering features for predictive models, and building interactive Power BI reports with DAX to track churn KPIs. Practical experience training and validating logistic regression and decision tree models using scikit-learn and evaluating performance with ROC-AUC and confusion matrices. Comfortable authoring and optimizing SQL queries for MySQL/PostgreSQL, automating preprocessing in Python (Pandas), and producing reproducible analysis in Jupyter/Colab. Certified in Google Data Analytics and trained via a 360DigiTMG data analytics program. Seeking an entry-level Data Analyst role where I can apply analytics and visualization skills to improve retention and revenue outcomes.

Education

Kakinada Institute of Engineering & Technology
Master of Computer Applications (MCA) • Andhra Pradesh, India • 2024 – 2026
Sri Ravi Degree College
Bachelor of Science in Computer Science • Andhra Pradesh, India • 2021 – 2024
Junior Ravi College
Board of Intermediate Education (12th - MPC) • Andhra Pradesh, India • 2019 – 2021

Technical Skills

Programming Language: Python,SQL
Databases: MySQL
Version Control & Development Tools: Jupyter Notebook,Google Colab,Git,GitHub
Data Analysis & Visualization: Pandas,NumPy,Matplotlib,Seaborn,Power BI,DAX,Microsoft Excel,A,B Testing Concepts
Machine Learning & AI: Logistic Regression,Decision Trees,K-Means,Clustering
AI/ML Frameworks & Libraries: scikit-learn
MLOps: Feature Engineering

Projects

Bank Customer Churn Analysis
Tools Used: SQL, Power BI, DAX, Microsoft Excel, Python, Pandas
  • Analyzed 10,000+ bank customer records across 10+ features to identify behavior signals and high-risk churn segments using SQL and Python.
  • Built a Power BI dashboard with multiple visualizations and 10+ DAX measures to track churn KPIs and product-level retention performance.
  • Derived business insights—such as 3× higher churn among inactive customers and stronger retention among high-balance customers—to prioritize retention campaigns.
Customer Shopping Behavior Analysis
Tools Used: Python, Pandas, NumPy, Matplotlib, Seaborn, SQL, Power BI, A, B Testing Concepts
  • Performed EDA on 3,900+ transactions to uncover purchasing patterns, product performance and discount impact using Python (Pandas, NumPy).
  • Engineered 5+ behavioral features and wrote 10+ SQL queries to support segmentation and cohort analysis for marketing decisions.
  • Built an interactive Power BI dashboard to present customer segments, sales KPIs and revenue insights and applied A/B testing concepts to evaluate promotion effectiveness.

Certifications

Data Analytics Program — 360DigiTMG • Jan–Aug 2025
Advanced SQL & MySQL Certification — CTEs
Google Data Analytics Professional Certificate — Coursera • 2024

Achievements

  • Authored 100+ SQL queries during internship: Built and optimized queries for data extraction, joins, aggregations and analytical reporting.
  • Solved 250+ SQL problems: Practiced complex joins, window functions and query optimization exercises to strengthen SQL proficiency.

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