Shreyaswini P
Bangalore
Summary
Results-driven data analytics specialist with strong focus on team collaboration and adaptability. Skilled in data modeling, statistical analysis, and machine learning to drive actionable insights and business growth. Reliable and flexible, consistently delivering high-impact solutions in dynamic environments. Known for problem-solving abilities and clear communication with both technical and non-technical stakeholders.
Overview
4
4
years of professional experience
1
1
Certification
Work History
Data Analytics Engineer
Sasken Technologies
10.2024 - Current
- Developed data pipelines to extract, transform, and load (ETL) large datasets for analysis.
- Collaborated with cross-functional teams to identify business requirements and deliver actionable insights.
- Utilized SQL and Python to analyze complex datasets, ensuring accuracy in reporting outcomes.
- Implemented data visualization tools to create dashboards that enhance decision-making processes.
Project Coordinator
Tata Consultancy Services (TCS)
03.2022 - 05.2024
- Coordinated internal projects, liaising between project stakeholders and technical teams.
- Managed testing and deployment activities, ensuring seamless application deployment to client environments.
- Analyzed deployment data to identify trends, patterns, and insights, facilitating strategic business decisions.
- Enhanced Excel and Power BI skills through regular reporting activities, providing valuable data insights to requesters and internal stakeholders.
- Played a key role in creating dashboards to monitor PC performance and network status, significantly improving operational efficiency.
Data Analyst
Tata Consultancy Services (TCS)
09.2021 - 05.2024
- Extracted data from Azure SQL DB and Azure Blob Storage, utilizing Power BI for effective data visualization and analysis.
- Developed DAX queries to create custom tables, calculated columns, and measures, enhancing data analysis capabilities.
- Designed and built interactive reports and dashboards using Power Pivot, Power BI, and Power Query.
- Leveraged Python libraries such as Pandas, NumPy, Matplotlib, and Seaborn to generate visually appealing and insightful data representations.
- Applied SQL skills to create tables, clean data, and retrieve information, ensuring data accuracy and quality.
- Demonstrated proficiency in Excel functions including VLOOKUP, HLOOKUP, LOOKUP, and pivot tables for in-depth data analysis.
- Utilized data modeling techniques to design efficient and scalable data structures for optimal analysis and reporting capabilities.
- Performed thorough data cleaning processes, employing industry best practices to enhance data accuracy and reliability.
Education
M. Tech. - Data Science And Artificial Intelligence
PES University
Bengaluru, India09-2026
B. E. - Computer Science
Visvesvaraya Technological University
Mysore, Karnataka, India01.2021
Skills
- Data Analysis: SQL, Python (Pandas, NumPy)
- Data Visualization: Microsoft Power BI, Excel, Tableau, Matplotlib, Seaborn
- Statistical Analysis: Python (SciPy, StatsModels), Excel
- Data Cleaning and Preparation: Python (Pandas, NumPy), Excel
- Database Management: SQL, MySQL
- Machine Learning: Python (scikit-learn)
- ETL (Extract, Transform, Load): SQL, Python (Pandas)
- Programming Languages: Python, MySQL, R (Basics)
- Cloud: AWS (S3, Redshift, Glue, Athena, Kinesis)
- Version Control & CI/CD: GitHub, CI/CD Pipelines(GitLab)
- Communication and Presentation: PowerPoint, Word, Tableau, Power BI
- Soft Skills: Attention to detail, Planning, Organization, Creative Problem-Solving, Teamwork and Collaboration, Active Listening, Adaptability, Analytical and Critical Thinking, Leadership, Time Management, Emotional Intelligence, Conflict Resolution, Customer Service
Projects
Project Description: Key Achievements:
Predictive Maintenance for Industrial Equipment
This project leverages machine learning to predict equipment failures in a manufacturing plant using sensor data. The goal is to predict failures in advance, allowing for preventive maintenance and minimizing downtime.
- 90% Accuracy: Predicted equipment failures with 90% accuracy, reducing unscheduled downtime by 30%.
- Cost Reduction: Cut maintenance costs by 20% by optimizing maintenance schedules.
- Increased Uptime: Improved equipment uptime by 25% through proactive maintenance alerts.
- Key Insights: Identified critical failure indicators like temperature spikes and vibration patterns.
- Real-time Monitoring: Developed a dashboard for real-time failure predictions and maintenance scheduling.
Certification
- Architecting with Google Compute Engine Specialization - Coursera
- Machine Learning Specialization - Coursera
- Python for Everybody Specialization - Coursera
- SQL for Data Science Specialization - Coursera
Languages
English [Fluent]
Kannada [Native]
Hindi [Intermediate]
Timeline
Data Analytics Engineer
Sasken Technologies
10.2024 - Current
Project Coordinator
Tata Consultancy Services (TCS)
03.2022 - 05.2024
Data Analyst
Tata Consultancy Services (TCS)
09.2021 - 05.2024
M. Tech. - Data Science And Artificial Intelligence
PES University
B. E. - Computer Science
Visvesvaraya Technological University