Rohit wamane

75 · Very Good

About

Detail-oriented data professional with hands-on experience in data analysis, machine learning, and dashboard development. Proficient in Python, SQL, and Power BI, with a strong ability to extract actionable insights from complex datasets. Passionate about solving real-world problems through data storytelling, automation, and predictive modeling.

Skills & Expertise (20)

SQL Advanced

8.0/10

Years Exp

Power BI Advanced

8.0/10

Years Exp

Python Advanced

8.0/10

Years Exp

Facebook Prophet Advanced

8.0/10

Years Exp

XGBoost Advanced

8.0/10

Years Exp

ARIMA Advanced

8.0/10

Years Exp

Exploratory data analysis Advanced

8.0/10

Years Exp

K-Nearest Neighbors Intermediate

7.5/10

Years Exp

scikit-learn Intermediate

7.5/10

Years Exp

Seaborn Intermediate

7.0/10

Years Exp

Excel Intermediate

7.0/10

Years Exp

MySql Intermediate

7.0/10

Years Exp

Visual Studio Code Intermediate

7.0/10

Years Exp

Jupyter Notebook Intermediate

7.0/10

Years Exp

Google Colab Intermediate

7.0/10

Years Exp

Git Intermediate

7.0/10

Years Exp

GitHub Intermediate

7.0/10

Years Exp

Matplotlib Intermediate

7.0/10

Years Exp

Pandas Intermediate

7.0/10

Years Exp

NumPy Intermediate

7.0/10

Years Exp

Work Experience

End-to-End Dashboard Development

Pizza Sales

Mar 2025 - Mar 2025

Designed and developed an interactive Power BI dashboard to analyze key sales metrics (Total Revenue, Total Orders, Pizzas Sold, and Average Order Value) from raw transactional data. Utilized SQL (aggregation, grouping, and date functions) to extract KPIs and identify sales trends across days, months, pizza categories, and sizes, enabling data-backed decision-making. Implemented data preprocessing and transformation using Excel and SQL for clean data ingestion into Power BI, ensuring accuracy and consistency of insights. Delivered actionable visual insights such as top-selling pizzas, category performance, and sales distribution, improving business strategy and revenue forecasting.

Time Series Forecasting and Sales Analysis

Walmart Dataset

Jan 2025 - Jan 2025

Achieved accurate 12-week store-level sales forecasts by developing and fine-tuning ARIMA, XGBoost, and Facebook Prophet models. Conducted advanced exploratory data analysis (EDA) to uncover seasonal patterns, regional performance, and economic influences (CPI, unemployment). Enhanced forecasting reliability by 21% through rigorous feature engineering, outlier treatment, and model optimization. Delivered actionable insights via visualizations in Matplotlib and Seaborn to support inventory planning and revenue management.

Content-Based and Collaborative Filtering

Movie Recommender System

Dec 2024 - Dec 2024

Built a personalized movie recommendation engine leveraging collaborative and content-based filtering to analyze user viewing patterns and preferences. Processed and cleaned 50K+ user ratings and movie metadata, improving data reliability by 37% and enabling efficient model training. Implemented cosine similarity and K-Nearest Neighbors (KNN) algorithms using Scikit-learn, achieving a Top-5 recommendation accuracy of 93%. Enhanced user satisfaction and content discoverability, reducing average search time by 42% and improving engagement metrics significantly.