Deepti Verma

Data Analyst

Kanpur, India 1+ yrs exp 88 · Excellent

About

Data Analyst with experience in large-scale data analysis, statistical modeling, and forecasting. Skilled in SQL, Python, Power BI, Excel, and machine learning techniques for predictive analytics and business intelligence. Proven ability to analyze 250K+ records, identify key trends, build forecasting models, and deliver actionable insights that support strategic decision making.

Skills & Expertise (27)

Python Intermediate

6.8/10

Years Exp

SQL Intermediate

6.5/10

Years Exp

Pandas Intermediate

6.5/10

Years Exp

XGBoost Intermediate

6.5/10

Years Exp

NumPy Intermediate

6.0/10

Years Exp

Excel Intermediate

6.0/10

Years Exp

scikit-learn Intermediate

5.8/10

Years Exp

LSTM Intermediate

5.5/10

Years Exp

ARIMA Intermediate

5.5/10

Years Exp

Power BI Intermediate

5.5/10

Years Exp

DBSCAN Intermediate

5.0/10

Years Exp

Hierarchical Clustering Intermediate

5.0/10

Years Exp

ARIMAX Intermediate

5.0/10

Years Exp

SARIMA Intermediate

5.0/10

Years Exp

K-Means Intermediate

5.0/10

Years Exp

PyTorch Intermediate

5.0/10

Years Exp

TensorFlow Intermediate

5.0/10

Years Exp

Streamlit Beginner

4.5/10

0.5

Years Exp

Delta Lake Databricks FAISS LangChain statsmodels PySpark NLP GAN CNN

Work Experience

Data Science Intern (Time Series Analysis)

Energy Analytics Lab, IIT Kanpur

May 2025 - Jul 2025

Evaluated 250K+ DAM electricity price records to identify temporal patterns and market volatility. Performed feature engineering (lags, rolling statistics, external variables) to improve model performance. Assessed anomaly detection techniques to identify and handle outliers in electricity price data. Improved forecasting models (LSTM, ARIMA, SARIMA, XGBoost), with XGBoost achieving the lowest RMSE.

M.Tech Thesis

IIT Kanpur

Jan 2025 - May 2026

Constructed a petrol price forecasting framework using 2017–2025 monthly data and microeconomic, policy, and energy indicators. Applied Hierarchical Regression, ADF, VIF, and Granger Causality analysis to identify significant price drivers. Developed and compared ARIMA, ARIMAX, and Random Forest models using RMSE evaluation.