Data Analyst Machine Learning

VARUN UPADHYAY

DATA ANALYST

+1-416-***-**** ****************@*****.*** Toronto, Ontario Linkedin PROFESSIONAL SUMMARY

Highly motivated and detail-oriented fresher with a strong foundation in Business and Data Analytics. Proficient in Microsoft Excel for data preparation, analysis, and visualization, with hands-on experience in statistical methods and data manipulation. Recently completed a Google Certification in Data Analysis gaining practical exposure to working with datasets, uncovering insights, and presenting findings effectively. Equipped with an analytical mindset, a passion for solving business problems, and a commitment to continuous learning. Enthusiastic about leveraging data-driven approaches to support decision-making and contribute to the success of a dynamic, growth-oriented team. EDUCATION

● Lambton College city, Ontario Jan’2024 – Aug’2025 CGPA-2.8 Post Graduate Certificate in Artificial Intelligence & Machine Learning

● CHARUSAT City, India Jun’2020 – May’2023 CGPA-8 Bachelor of Science in Information Technology (Data Science) WORK EXPERIENCE

Data Analyst

ZMARK SOLUTIONS PRIVATE LIMITED Gujarat, India Jun’23 – Dec’23

● Spearheaded the requirement gathering process by engaging stakeholders and documenting business needs in user stories, streamlining workflows and driving a reduction in project turnaround time.

● Delivered timely and accurate reports to management, providing actionable insights that improved decision- making processes by 35%.

● Designed and implemented ETL pipelines to facilitate seamless data migration from operational systems into the staging area (Source to Staging) and into the Data Warehouse, ensuring data integrity, accuracy, and reliability.

● Optimized complex data transformations by leveraging Informatica PowerCenter, including Source Qualifier, Lookup, Update Strategy, Aggregator, Expression, Filter, and Joiner transformations, resulting in efficient data processing and reduced latency.

● Addressed data integration challenges by standardizing ETL processes and improving data workflows, which enhanced data availability for analytics and reporting teams.

● Developed interactive Power BI Reports and Dashboards integrated with SQL Server to provide stakeholders with real-time insights and actionable intelligence, enabling improved business performance and decision-making.

● Collected and analyzed customer interaction data during peak retail hours to identify purchasing trends and optimize product placement strategies.

● Utilized customer feedback to identify pain points and collaborated with stakeholders to improve product presentation and customer engagement.

● Supported promotional campaign analysis by tracking KPIs such as foot traffic conversion rates and promotion- driven sales growth, contributing to data-informed marketing decisions.

● Generated weekly sales and customer behavior reports using Excel to assist management in refining inventory and merchandising strategies for improved ROI.

PROJECTS

1. Netflix Dataset Analysis

Problem Statement:

• Understand viewer preferences and trends on Netflix to identify popular genres, rating distributions, and content availability across countries.

Solution:

• Analysed the Netflix dataset to identify the distribution of shows by date added and genre.

• Used Power BI to develop interactive dashboards highlighting trends in ratings, popular genres, and country.

• Leveraged Excel for initial data cleaning and organization, ensuring dataset consistency.

• Conducted exploratory data analysis (EDA) using Python (Pandas, Matplotlib). 2. Sales Data Analysis for an E-Commerce Store

Problem Statement:

• Analysed sales data to uncover trends, identify top-selling products, and understand customer purchase behaviour.

Solution:

• Cleaned and structured sales data in Excel for analysis, identifying key variables such as product categories, sales regions, and revenue.

• Created visualizations in Power BI to showcase top-selling products, sales trends, and seasonal peaks.

• Used Python for EDA to calculate KPIs such as total sales, average transaction value, and customer retention rates. SKILLS

Data Analysis & Visualization: Pandas, NumPy, Matplotlib, Seaborn, Tableau, Excel, Machine Learning & AI: Scikit-learn, Regression, Classification, Clustering, NLP, Deep Learning (basics), Data Collection & Processing: Data Cleaning, Feature Engineering, Databases: MySQL, Vector Databases, Frameworks & Tools: Django, LangChain, Git, Jupyter Notebook, VS Code, Agile, Scrum, Data-modeling, Workflow Analysis, Dashboard design, Cloud & Deployment: AWS, Azure

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