Abhijeet Singh Pawar

Data Analyst | Data Scientist | Risk, Product & Business Analytics

📧 aspabhi31@gmail.com
🔗 LinkedIn
💻 GitHub

About Me

I am a Data Analyst with a strong focus on risk, product, business analytics, business insights, and automation.
I have hands-on experience building end-to-end analytics pipelines, predictive models, and executive dashboards using real-world datasets (20K–30K+ records).

My work spans retail analytics, credit risk modeling, customer behavior analysis, and machine learning, with an emphasis on interpretability and business impact.

Core Skills

Programming & Analytics

Python (Pandas, NumPy, Scikit-learn, PyTorch)
SQL (MySQL, PostgreSQL – CTEs, Window Functions, Subqueries)

Data Science & Modeling

Regression & Classification
Credit Risk Modeling (PD, Risk Bands)
Churn Analysis & Customer Segmentation
NLP (BERT-based Text Classification)
Model Validation (ROC-AUC, KS, Precision/Recall)

Business Intelligence & Automation

Power BI (Interactive Dashboards, KPI Tracking)
Advanced Excel (Pivot Tables, Power Query, Automation)
Data Cleaning, Validation & Reporting Automation

Experience

Vosyn — Data Analytics & Visualization Consultant

Remote | July 2025 – January 2026

Automated data cleaning, preprocessing, and validation workflows, reducing manual reporting effort by ~30%.
Built analysis-ready datasets and data pipelines to support dashboards and operational reporting.
Performed exploratory data analysis (EDA) to identify trends, anomalies, and data quality issues.
Developed and evaluated predictive models (Logistic Regression, Naive Bayes, BERT-based NLP classifiers).
Conducted comparative model analysis focusing on accuracy, interpretability, and business impact.

Featured Projects

🔹 Credit Card Credit Risk Modeling & Approval Strategy

Python | Risk Analytics
🔗 https://github.com/aspabhi31/credit-risk-project

Analyzed ~30,000 customer records to identify key drivers of default risk.
Built an interpretable Probability of Default (PD) scoring framework with Low / Medium / High risk bands.
Evaluated model performance using ROC-AUC (~0.70+) and KS (~0.30+).
Designed PD-based approval cutoffs and simulated portfolio impact, reducing expected credit loss.

🔹 Retail Business Analytics & Customer Behavior

Python | SQL | Power BI
🔗 https://github.com/aspabhi31/retail-business-analytics

Built an end-to-end SQL analytics pipeline on ~20K retail transactions.
Identified that top 20% of customers contribute ~75% of total revenue.
Flagged ~5% of customers at churn risk using inactivity-based analysis.
Modeled customer lifetime value (CLV) and repeat-purchase behavior.
Developed interactive Power BI dashboards for KPI and executive reporting.

🔹 SaaS Product & Revenue Analytics

Python | SQL | Power BI
🔗 https://github.com/aspabhi31/SaaS-Product-Revenue-Analytics

Built end-to-end SaaS Product Analytics project using MySQL, analyzing funnel conversion, cohort retention, MRR, ARPU, churn (~10%), and LTV (~₹13.1K).
Conducted channel-level revenue segmentation, identifying Referral as highest conversion source and Paid Ads as highest ARPU driver.
Designed cohort-based retention framework to evaluate user stickiness and long-term revenue sustainability.
Delivered data-driven recommendations to optimize acquisition strategy and improve monetization efficiency.

🔹 Predictive Risk Classification – Vehicle Damage Detection

PyTorch | Transfer Learning | Optuna
🔗 https://github.com/aspabhi31/Vehicle-Damage-Detection

Developed a ResNet50-based classification model to assess vehicle damage across six categories.
Applied data augmentation and hyperparameter optimization to improve robustness.
Evaluated performance using confusion matrix, precision/recall, and error analysis.

🔹 Time Series & Regression – Energy Output Prediction

Scikit-learn
🔗 https://github.com/aspabhi31/Energy-Output-Prediction

Built regression and forecasting models on multi-year sensor data.
Optimized learning rates and convergence to minimize MSE.
Demonstrated structured modeling and transparent evaluation.

🔹 US Debt Tracker Analysis

Advanced Excel
🔗 https://github.com/aspabhi31/US-Debt-Tracker-Analysis

Analyzed 7,000+ daily records to identify long-term debt trends.
Identified a 26% spike in 2020 and projected 12–13% annual growth.

Education

Memorial University of Newfoundland, Canada
MASc in Computer Engineering | GPA: 3.81 / 4
2022 – 2024

Thapar University, India
B.Tech in Electronics (Instrumentation & Control Engineering)
2017 – 2021

Certifications

Data Science & Machine Learning — Coding Ninjas (2024–2025)
Artificial Intelligence — C-DAC (2021–2022)

What I’m Looking For

Data Analyst / Data Scientist roles
Risk Analytics & Business Intelligence positions
Entry roles
Teams that value data-driven decision-making

⭐ If you find my work interesting, feel free to connect or explore my repositories!