Shreyas Pradeep
Navi Mumbai
Summary
In dynamic and fast-paced environment, developed skills in data analysis, problem-solving, and strategic thinking. Excel in interpreting complex data sets and delivering actionable insights to support business objectives. Seeking to transition into new field where these transferrable skills can drive meaningful impact and innovation.
Overview
4
4
years of professional experience
Work History
Working Student Data Analyst
Lime
01.2023 - 11.2024
- In my role in the e-commerce industry, I led key initiatives to revolutionize the e-commerce customer experience, achieving significant improvements in order processing speed, customer satisfaction, and revenue growth. Through innovative analytics and automation, I not only halved the time for report generation but also reduced data inaccuracies by 30%, greatly boosting operational efficiency.
- Collaborating across teams, I developed real-time dashboards for strategic insights and streamlined data workflows to enhance market adaptability. My commitment to data quality further ensured reliable financial analysis, underpinning the company’s expansion in the e-commerce sector.
- I also engaged in Market Data Analysis, partnering with the Sales and Customer Lifecycle Management (CLM) teams to derive valuable insights. Utilizing my expertise, I developed Machine Learning (ML) models to forecast market trends and analyze customer patterns, thereby improving sales tactics and customer retention efforts.
- Additionally, I enhanced operational workflows by implementing automation through Power Automate, VBA, and Python, increasing productivity among diverse teams.
Application Support Engineer
Impact Infotech Pvt Ltd
02.2021 - 08.2022
- Nationwide Mobility Support: Provided 16/7 support to 7.5 lakh retailers, streamlining the order-to-activation journey with technological initiatives like BBOT’s, user tools, and process redesign, achieving 92% L1 resolution and 85% first-call/first-time resolution rates.
- Leadership & Collaboration: Led teams to address technical issues, analyze client requirements, and enhance customer quality and value, focusing on problem management, incident management, and IT operations.
- Service Desk Expertise: Demonstrated expertise in service desk and incident management with a robust understanding of best practices and operational excellence.
Education
Masters - Data Science
International University of Applied Sciences
04.2025
Post Graduate Diploma - Data Science (Python, Statistics, Big Data, Machine Learning, Business Intelligence, Deep Learning, SQL)
International Institute of Information Technology, Bangalore
Bangalore, India07.2022
Bachelor’s - information technology
SIES College of Arts, Science and Commerce
Mumbai, India10.2020
Skills
- Languages: Python, SQL
- Tools: MS Excel, Tableau, Power BI(DAX), Jira, HPSM, SAP, MS Office, SharePoint, Confluence, Git
- Operating system: Linux, Windows
- Functions: Power Query, Data Visualization
Languages
English – Business Fluent
German – Intermediate
German level – B1
Timeline
Working Student Data Analyst
Lime
01.2023 - 11.2024
Application Support Engineer
Impact Infotech Pvt Ltd
02.2021 - 08.2022
Post Graduate Diploma - Data Science (Python, Statistics, Big Data, Machine Learning, Business Intelligence, Deep Learning, SQL)
International Institute of Information Technology, Bangalore
Bachelor’s - information technology
SIES College of Arts, Science and Commerce
Masters - Data Science
International University of Applied Sciences
Projects
Credit Card Fraud Detection:
• In a banking-focused capstone project, I developed a machine learning solution to predict credit card fraud, addressing class imbalance issues. I selected and fine-tuned models, enhancing their accuracy in detecting fraudulent transactions.
• This four-week project sharpened my skills in data analysis, model selection, and hyperparameter tuning, alongside deepening my understanding of the banking industry’s challenges and customer trust importance.
Lead Scoring Case Study:
• In this project for X Education, I developed a logistic regression model to score and identify ‘Hot Leads’-potential customers likely to convert- out of 9,000+ data points, aiming to boost the lead conversion rate from 30% to 80%.
• The project deliverables included a detailed Python script, a solution document, a comprehensive presentation, and a summary report, showcasing my analytical approach and findings.
Telecom Churn Case Study:
• This project focuses on predicting customer churn in the telecom industry by analyzing high-value customer data to identify churn indicators. • It involves data preparation, feature engineering, handling class imbalance, and building predictive models to both forecast churn risk and understand key predictors, guiding retention strategies.
Master Thesis- A predictive analysis using Time Series Maintenance:
• Objective of Predictive Maintenance: The thesis explores predictive maintenance using time series analysis, focusing on improving reliability, efficiency, and cost-effectiveness in industrial equipment. It compares models like ARIMA and LSTM, emphasizing IOT integration for real-time data acquisition and actionable insights.
• Key Findings: ARIMA excels with linear and stationary data, while LSTM handles non-linear, sequential data with long-term dependencies. IOT enhances real-time predictions, reducing downtime and maintenance costs while increasing equipment longevity.
• Challenges and Recommendations: Addresses issues like data quality, model integration, and cost considerations, advocating for robust data governance and IOT-driven strategies to optimize predictive maintenance systems.