PAVULURI MALLESWARI
Data ScienceAI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Data Science with less than a year in Python, SQL & Power BI, specializing in end-to-end analytics w
Results-driven Data Analyst with hands-on training from BossCoder Academy and a strong foundation in Python, SQL, Power BI, and Tableau. Experienced in end-to-end analytics workflows - from data cleaning and exploratory data analysis to dashboard development and business storytelling. Completed real-world projects in e-commerce analytics and customer segmentation. Strong background in machine learning and AI/ML model building with practical project deployments. MCA graduate from KL University (GPA 8.5) with certifications from Microsoft, Anthropic, and AWS. Passionate about turning data into decisions.
KL University
Master of Computer Applications (MCA)
August 1, 2023 – June 30, 2025
Govt. Women's College
Bachelor of Science (B.Sc)
August 1, 2020 – June 30, 2023
Customer Segmentation Analysis – Behavioral Clustering
June 19, 2026 – Present
Applied K-Means clustering on RFM (Recency, Frequency, Monetary) features to segment customers into distinct behavioral groups. Performed feature engineering, scaling, and elbow-method analysis to determine the optimal number of clusters. Visualized customer segments using Seaborn and Tableau to clearly present segment profiles and business recommendations. Identified high-value customer segments and churn-risk groups, enabling targeted retention and upsell strategies.
E-commerce Data Analysis – Sales & Revenue Insights
June 19, 2026 – Present
Analyzed 100K+ transaction records to identify top-selling products, revenue trends, seasonal patterns, and customer purchase behavior. Performed data cleaning and transformation (handling nulls, duplicates, type conversions) to ensure analysis-ready datasets. Created an end-to-end Power BI dashboard with KPIs including total revenue, order volume, average order value, and category-wise performance. Delivered actionable insights on peak sales periods and underperforming categories, supporting data-driven inventory and marketing decisions.
Facial Recognition System – ML Pipeline & Deployment
June 19, 2026 – Present
Preprocessed facial image datasets and implemented CNN and LBPH face recognition algorithms using dlib. Evaluated model performance (accuracy, precision, recall) and deployed a real-time attendance management interface.
Crop Disease Detection – ML & Computer Vision
June 19, 2026 – Present
Built end-to-end ML pipeline: data collection, EDA, feature engineering, model training (CNN, SVM, Random Forest), and evaluation. Achieved high classification accuracy across 20+ crop disease classes using TensorFlow CNN on the PlantVillage dataset. Deployed a real-time prediction interface via Flask/Streamlit for actionable disease identification.
Claude AI Course
Anthropic
January 1, 2026 – Present
Data Analyst Course
BossCoder Academy
July 1, 2025 – Present
MySQL Certification
AWS
January 1, 2025 – Present
Python Development
Microsoft
January 1, 2025 – Present
Cultural Fit Analysis
The candidate's academic projects demonstrate a breadth of interest across various data science applications (business analytics, computer vision, machine learning deployment). The certifications from diverse organizations (Microsoft, AWS, Anthropic) also show a proactive approach to learning and adapting to new technologies. This indicates a potential for a growth-oriented mindset, which aligns well with a dynamic technical culture. However, the lack of professional experience makes it challenging to assess cultural fit in a corporate environment.
Soft Skills & Operational Fit
The candidate's project descriptions highlight an ability to translate technical analysis into business recommendations and create user-friendly interfaces, suggesting good problem-solving and communication skills. The academic projects also imply an ability to work independently and manage project lifecycles. However, without direct work experience or specific examples of collaboration, it's difficult to fully assess operational fit and soft skills like teamwork or conflict resolution.