Vivek Kumar

Data Analyst

Bengaluru, Karnataka, India3 yrs 11 mos experience

Most Likely To Switch

Key Highlights

2+ years of experience in data analysis.
Proficient in SQL, Python, and Machine Learning.
Expert in real-time predictive analysis.

Stackforce AI infers this person is a Data Analyst with expertise in analytics and predictive modeling.

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Skills

Core Skills

Data AnalysisPricing AnalysisData VisualizationMachine Learning

Other Skills

Actuarial ScienceAnalytical SkillsAnalyticsData MiningGoogle Data StudioLogistic RegressionMarket AnalysisMarket SegmentationMicrosoft ExcelPricing StrategyPython (Programming Language)SQLStatistical ModelingTableauUnderwriting

About

Seasoned analytics professional with 2+ years of specialized experience in data analysis focusing on GHI data, risk analysis, SWOT analysis, live predictive analysis, and real-time stock price updates. Proficient in SQL, Python, MS Excel, Machine Learning and Power BI. Committed to driving informed decision-making and Adept at leveraging analytical skills to contribute in any technology-focused team

Experience

Acko (ext)

Analyst

Mar 2024 – Present · 2 yrs · On-site

Pricing AnalysisActuarial ScienceUnderwritingMicrosoft ExcelSQLData Analysis

Nu10

Data Analyst

Jan 2023 – Feb 2024 · 1 yr 1 mo · Bengaluru, Karnataka, India · On-site

TableauVBA ExcelPricing AnalysisData AnalysisMicrosoft ExcelPricing Strategy+3

Almabetter

4 roles

Customer Segmentation

May 2022 – Jun 2022 · 1 mo

1. Built a clustering model using K-means to identify major customer segments on demographic and psychographic-based data to optimize impact of marketing
campaigns.
2. Engineered features to obtain new features such as RFM, RFMGroup, and RFMScore
for getting more details about the customers' purchasing behaviour.
3. Evaluated the optimal clusters using Silhouette score and Elbow method and leveraged
the visualization library t-SNE for multidimensional scaling to visualize and validate the
inter-cluster separation and intra-cluster similarities.
4. Deployed K-Means clustering and got the optimal number of clusters equal to 2 having
the highest silhouette score of 0.39.

Logistic RegressionData Analysis

Credit Card Default Prediction

Apr 2022 – May 2022 · 1 mo

1. Developed a binary classification model using algorithms such as Logistic Regression, SVC and XGBoost to predict whether a customer will default on credit card payments.
2. Extraction of features from the customers datasets followed by data analysis using
Statistical and Visualization tools.
3. Implemented SMOTE boosting to oversample the minority class observations and
carried out hyperparameter tuning.
4. Deployed XGBoost classifier to predict whether a customer will default and achieved
highest test accuracy score of 87% and AUC is 0.873.

Logistic RegressionData Analysis

Bike Sharing Demand Prediction

Mar 2022 – Apr 2022 · 1 mo

1. Developed a regression model using algorithms such as Random Forest and XGBoost
to predict the hourly demand of bikes and reduced the public waiting time.
2. Designed the data pipeline to work on, understood the impact of features such as time of the day, weather condition, holidays and engineered important features for model.
3. Imputed missing values, encoded categorical columns, handled outliers, checked multicollinearity and experimented with different models.
4. Performed hyperparameter tuning techniques such as GridSearch CV and achieved R2
score of 92% using XGBoost model and reduced the public waiting time significantly.

Data Analysis