Leela Sai Venkat

Junior Data Analyst

INDIA.

About

HR Analyst turned Business Analytics professional with proven expertise in data analysis, HR operations, and workforce analytics. Skilled in Python, SQL, Tableau, Power BI, Excel, and R, with hands-on experience in predictive modeling, AI-powered analysis, and dashboard development. Completed an MBA in Business Analytics, equipping me with strong technical and strategic skills. Recognized twice as Best Employee at Trigent Software for delivering actionable data insights that improved HR decision-making. Highly proficient in applying Artificial Intelligence tools to enhance data processing, visualization, and business insights.data-driven recommendations that optimize human capital performance and support key business decisions.

Work

Trigent Software - Professional Services

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HR Analyst

Bengaluru, Karnataka, India

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Summary

Roles and Responsibility: • End-to-end IT Recruitment. • Candidate Management using ATS software. • Headhunting. • Conduct data analysis to support HR initiatives and decision making. • Create and analyze reports on key HR metrics such as employeeturnover, retention, and engagement. • Collaborate with HR team members to identify trends and insights from data analysis. • Participate in developing and implementing HR strategies based on datadriven insights. • Support HR projects and initiatives by providing data and insights to inform decision making. • Monitor and track HR metrics to ensure accuracy and consistency in reporting. • Assist with recruitment and onboarding processes by analyzing data on candidate pipelines and new hire performance. • Provide analytical support for HR programs and initiatives, such as talent management, diversity and inclusion efforts, and employee development. • Ensure that HR records and data management practices comply with legal and regulatory requirements. • Assist in forecasting future staffing needs based on analysis of current workforce trends and organizational goals.

Education

Gems College

Bangalore, Karnataka, India
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Master of Business Administration (MBA) Business Analytics Grade:

St. Paul's Degree & PG College

Hyderabad, Telangana, India
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Bachelor of Business Administration (BBA) Business Administration Grade: 7.43 CGPA

Awards

Best Employee

Trigent Software - Professional Services

Recognized for outstanding performance and contributions to the team.

Best Employee

Trigent Software - Professional Services

Recognized for outstanding performance and contributions to the team.

Certificates

Power BI, Python

Grow AI

Python, SQL, Table, Excel, MoongoDB

Klynveld Peat Marwick Goerdeler (KPMG) Certificate

Skills

Programming

Python, Pandas, NumPy, Seaborn, Matplotlib, R.

Databases

SQL, MongoDB.

Data Visualization

Tableau, Power BI, MS Excel.

Analytics

Data Cleaning, Statistical Modeling, Data Reporting, Dashboard Development.

Machine Learning

Logistic Regression, Decision Tree, Classification Metrics, Accuracy, F1 Score, Precision, Recall.

Soft Skills

Analytical Thinking, Problem Solving, Communication & Collaboration, Attention to Detail, Time Management, Business Acumen.

Projects

Employee Performance & Attrition Analysis

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Summary

Objective: Improve HR retention and workforce planning through predictive analytics. Tools & Tech: Python (Pandas, NumPy, Seaborn, Matplotlib), SQL, Tableau, Power BI, Excel, AI tools. Key Contributions: Cleaned and processed 10,000+ employee records, ensuring accuracy in performance and attrition data. Conducted exploratory data analysis (EDA) using Python & SQL to identify key attrition factors (tenure, salary, job role, engagement scores). Built predictive models (Logistic Regression, Decision Tree) achieving 82% accuracy in attrition forecasting. Designed interactive dashboards in Tableau & Power BI to visualize attrition risk by department, tenure, and job role. Applied AI tools to automate reporting and accelerate data interpretation. Impact: Provided HR leadership with data-backed insights, leading to a 12% improvement in employee retention over 6 months.

Credit Card Default Prediction

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Summary

Objective: Reduce financial risk by predicting customers likely to default. Tools & Tech: Python (Scikit-learn, Pandas, NumPy), R, Tableau, Excel. Key Contributions: Collected and cleaned 20,000+ customer records including demographic, financial, and repayment history. Applied feature engineering to create variables (debt-to-income ratio, repayment patterns, credit utilization). Implemented classification models (Logistic Regression, Decision Tree, Random Forest) to predict default probability. Achieved a 15% reduction in misclassification rate compared to baseline models. Designed segmentation reports to identify high-risk customer groups for targeted interventions. Impact: Helped the financial institution strengthen risk assessment and reduce potential credit losses.