Yash Mishra

Data Analyst

Lucknow 0+ yrs exp 71 · Very Good

About

No bio added yet

Skills & Expertise (26)

SQL Intermediate

5.5/10

0.1

Years Exp

JavaScript Intermediate

5.5/10

0.1

Years Exp

Google Apps Script Intermediate

5.5/10

0.1

Years Exp

VS Code Intermediate

5.5/10

0.1

Years Exp

Excel Intermediate

5.5/10

0.1

Years Exp

Matplotlib Intermediate

5.5/10

0.1

Years Exp

NumPy Intermediate

5.5/10

0.1

Years Exp

Pandas Intermediate

5.5/10

0.1

Years Exp

Data Visualization Intermediate

5.5/10

0.1

Years Exp

Python Intermediate

5.5/10

0.1

Years Exp

Exploratory data analysis Intermediate

5.5/10

0.1

Years Exp

Git Beginner

2.5/10

0.1

Years Exp

Recharts Beginner

2.5/10

0.1

Years Exp

React.js Beginner

2.5/10

0.1

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HTML Beginner

2.5/10

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FastAPI Beginner

2.5/10

0.1

Years Exp

scikit-learn Beginner

2.5/10

0.1

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Jupyter Notebook Beginner

2.5/10

0.1

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Docker Beginner

2.5/10

0.1

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TensorFlow Beginner

2.5/10

0.1

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Power BI Beginner

2.5/10

0.1

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Seaborn Beginner

2.5/10

0.1

Years Exp

Feature Engineering Beginner

2.5/10

0.1

Years Exp

Model Evaluation Beginner

2.5/10

0.1

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Classification Models Beginner

2.5/10

0.1

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Statistical Analysis Beginner

2.5/10

0.1

Years Exp

Work Experience

Finance Automation Intern

NOISE

Mar 2026 - Present

Led the PNL Automation project, driving end-to-end automation of finance workflows and cutting manual processing effort by ˜12 days/month. Built custom dashboards using Google Apps Script, HTML, and JavaScript, giving stakeholders real-time visibility into processed financial data and KPIs. Leveraged Claude AI to accelerate automation development, debugging, and technical documentation.

Data Science Intern

IBM

Feb 2024 - Mar 2024

Performed Exploratory Data Analysis (EDA) on structured business datasets to uncover trends and generate actionable business insights. Cleaned, transformed, and analyzed datasets using Python (Pandas, NumPy), improving data quality and analytical reliability. Applied feature engineering, preprocessing, and machine learning techniques, achieving an 18% improvement in model performance. Collaborated with cross-functional teams to interpret analytical results, validate models, and support data-driven decision-making.