Jul 2024 – Apr 2025 · 9 mos · Bangalore Urban, Karnataka, India · Hybrid

• I am a results-driven Senior Data Analyst worked with GChip team , where I specialize in building data-driven ecosystems that empower engineering and leadership teams to make impactful decisions.
• With strong expertise in tools like PLX Workflow, Looker Studio, BigQuery, Buganizer, GCB (Google Cloud Build), and Gmail APIs, I have built scalable data pipelines, dashboards, and automation solutions that directly support silicon development and chip lifecycle operations.
• In my role, I’ve:
• Automated PLX Workflows to reduce manual reporting and improve visibility across hardware design stages. These workflows are tailored to track OKRs, milestone completion, and data handoff across teams.
• Designed Looker Studio dashboards, including a real-time RTL (Register Transfer Level) dashboard, which delivers key chip development KPIs, enabling faster engineering reviews and better decision-making.
• Written high-performance SQL queries in BigQuery to power complex reporting and real-time data analysis, ensuring accuracy, scalability, and cost-efficiency by leveraging partitioning and clustering.
• Improved bug tracking and triaging by developing structured reporting systems in Buganizer, helping reduce recurring issues and aligning engineering focus toward preventive action.
• Integrated GCB metrics into dashboards for CI/CD performance monitoring. These insights have helped teams identify build-time bottlenecks and improve pipeline efficiency.
• Built Gmail-based alerting systems that automatically notify stakeholders about workflow status, anomalies, and action-required events—improving communication flow and reducing resolution time.
• I bring a strong balance of technical depth and business understanding, enabling me to serve as a critical bridge between engineering, data, and product stakeholders.

Aug 2021 – Jun 2024 · 2 yrs 10 mos · Bangalore · Remote

• Utilized SQL to extract, transform, and manipulate large datasets from
• diverse sources, enabling comprehensive analysis and reporting.
• Developed complex data visualizations and interactive dashboards using
• Tableau and Power BI, providing actionable insights to stakeholders and
• driving informed decision-making.
• Applied Python programming skills to perform data wrangling, statistical
• analysis, and predictive modeling, resulting in optimized business
• processes and improved forecasting accuracy.
• Implemented machine learning algorithms, including regression,
• classification, and clustering techniques, to uncover patterns and trends in
• data, driving strategic initiatives and enhancing operational efficiency.
• Leveraged MongoDB for data storage and retrieval in projects requiring
• flexible schema and scalability, ensuring efficient handling of semistructured and unstructured data.
• Collaborated cross-functionally with teams including marketing, finance,
• and operations to understand business requirements and translate them
• into data-driven solutions, contributing to organizational growth and
• success

Jan 2021 – Aug 2021 · 7 mos · Bengaluru, Karnataka, India · On-site

• #Contributed to data collection, cleaning, and preprocessing tasks to ensure the quality and reliability of datasets used for analysis.
• #Utilized Python and R programming languages to perform exploratory data analysis (EDA) and extract meaningful insights from large datasets.
• #Assisted in the development and implementation of machine learning algorithms for predictive modeling tasks, leveraging techniques such as regression, classification, and clustering.
• #Collaborated with senior data scientists to refine model performance through hyperparameter tuning and optimization techniques.
• #Created interactive visualizations using Tableau and PowerBI to communicate findings and trends to stakeholders effectively.
• #Conducted ad-hoc analyses and generated actionable recommendations to support business decision-making processes.
• #Demonstrated proficiency in SQL for data extraction, transformation, and loading (ETL) tasks.
• #Actively participated in team meetings, contributing ideas and insights to ongoing projects and discussions.

Jul 2019 – Nov 2020 · 1 yr 4 mos · Mumbai, Maharashtra, India · On-site

• I worked on real-world data projects to help teams make smarter decisions. My role focused on analyzing data, building models, and automating workflows.
• Used Python and SQL for data cleaning, analysis, and automation
• Built machine learning models for prediction and classification
• Created dashboards using Tableau and Seaborn to visualize insights
• Applied NLP techniques for sentiment analysis and text mining
• Automated reporting tasks to improve speed and accuracy
• Collaborated with cross-functional teams to solve business problems
• Gained hands-on experience with Jupyter Notebooks, Git, and cloud platforms
• Learned best practices in data ethics, reproducibility, and communication
• Participated in team meetings, sprint reviews, and presented findings
• Explored time-series forecasting and clustering techniques for deeper insights
• Documented workflows and maintained version control for reproducibility
• Focused on turning data into clear, actionable recommendations
• This internship gave me a strong foundation in data science and sparked my passion for solving real-world problems through data.