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Associate Data Scientist with 2+ years in Machine Learning & Statistical Modeling
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Assessing your cultural and operational fit
Data Scientist with strong foundation in Python, machine learning, and statistical modeling, skilled in applying data analysis techniques to solve real-world business problems. Experienced in working with large datasets, developing predictive models, and generating actionable insights. Strong analytical thinker with the ability to collaborate across teams and deliver data-driven solutions in dynamic environments.
Institute Of Professional Education And Research
MBA · Finance
August 1, 2017 – June 30, 2019
Esaf Small Finance Bank
Assistant Manager (Data Analyst)
January 1, 2023 – November 1, 2025
India
Financial Risk & Customer Behavior Analysis
November 1, 2025 – June 1, 2026
Implemented financial risk detection framework using Z-score anomaly detection, IQR-based thresholds, and balance volatility (standard deviation) to identify high-risk accounts and suspicious transaction behavior. Developed customer segmentation models based on activity level, transaction volume, and balance metrics, creating profiles like high-net inflow and high-frequency low-balance users to support decision-making. Conducted exploratory data analysis (EDA) and built transaction summaries using groupby, aggregation, and feature engineering, identifying key trends such as debit dominance and net cash outflow patterns.
View ProjectMarket Basket Analysis
November 1, 2025 – June 1, 2026
Performed customer behavior analysis using Python (Pandas, NumPy), including data cleaning, feature engineering, and EDA to identify purchasing patterns and risk factors. Implemented K-Means Clustering for customer segmentation, and optimized cluster selection using Elbow Method and Silhouette Score, improving model reliability and interpretability. Engineered features such as purchase frequency scaling and applied unsupervised machine learning techniques to classify customers into Frequent Buyers, Occasional Shoppers, and At-Risk segments. Conducted statistical analysis (correlation & ANOVA) and built visualizations (Matplotlib, Seaborn) to generate insights for improving retention and reducing cart abandonment.
View ProjectInternshala Data Science Professional Certificate
Internshala
June 1, 2026 – Present
Google Advanced Data Analytics Certificate
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's projects demonstrate initiative and a proactive approach to learning and applying data science techniques. The MBA in Finance combined with data science certifications and banking experience suggests a strong interest in applying analytical skills to business problems, which aligns well with a data-driven culture. The diversity of projects (market basket analysis, financial risk) indicates adaptability and a broad interest in different data challenges. However, the experience is primarily in a single domain (banking), and the projects are personal, which might limit exposure to diverse team dynamics and large-scale enterprise environments.
Soft Skills & Operational Fit
The candidate highlights strong analytical thinking, problem-solving, and collaboration skills. Experience in a banking environment suggests an ability to work with sensitive data and adhere to operational processes. The project descriptions indicate a structured approach to data analysis, from cleaning to visualization and insight generation. However, the resume does not provide specific examples of how these soft skills were applied in complex, cross-functional scenarios or under pressure, which would be expected for a senior role.