Chandra Shekhar Yanagandula
Hyderabad,India
Summary
Experienced Data Analyst with 4+ years of expertise in transforming complex data into actionable insights to support strategic decision-making. Skilled in data visualization tools like Tableau and Power BI, advanced SQL, Python, and statistical analysis.
Overview
5
5
years of professional experience
Work History
Senior Data Analyst
Howmet Aerospace
Pittsburgh, Pennsylvania
04.2024 - Current
- Company Overview: Howmet Aerospace is a global leader in the aerospace and defence industry, specializing in advanced materials and manufacturing technologies
- Cleaning, standardizing, and transforming raw data to ensure accuracy and consistency for analysis and developing complex data models to forecast potential scenarios, threat assessments, and operational outcomes
- Lead data analysis initiatives to optimize operational efficiency, product development, and strategic planning within aerospace and defense manufacturing at Howmet Aerospace
- Developed and maintained automated dashboards and reporting tools using Power BI, Tableau, and Looker to monitor key performance indicators (KPIs) for aerospace production and quality control
- Designed and optimized ETL pipelines using Informatica, Alteryx, and Talend to aggregate data from diverse sources, including production databases, inventory management systems, and supply chain platforms
- Implemented predictive analytics and machine learning models using Python, R, and scikit-learn to forecast demand for aerospace components, optimize inventory, and predict maintenance needs for critical manufacturing equipment
- Utilized SQL, PostgreSQL, and Oracle for data extraction, querying, and optimization from large-scale relational databases and data warehouses used in aerospace manufacturing
- Worked closely with the IT team to manage and troubleshoot data integration challenges across on-premises and cloud-based systems, including AWS and Google Cloud Platform
- Utilized Snowflake and other cloud data platforms for scalable data storage and real-time analytics of production, quality assurance, and product lifecycle data and implemented data visualizations to highlight trends in production efficiency, inventory management, and manufacturing quality control for the aerospace sector
- Optimized cloud infrastructure for data storage and processing, utilizing services such as AWS Redshift and Google Big Query to support large-scale data analytics
- Proficient in using Excel to build dynamic financial and operational models, analyse large datasets, and visualize trends for forecasting production and market demands
- Skilled in Python and its libraries such as Pandas, NumPy, Matplotlib, and Seaborn for data cleaning, manipulation, and statistical analysis to derive actionable insights from large datasets in aerospace manufacturing
- Extensive experience with Hadoop, Apache Spark, and Kafka for processing large-scale datasets, implementing real-time data streaming, and performing distributed data analytics to improve operational decision-making in the aerospace sector
- Managed and optimized Snowflake for cloud-based data storage and real-time analytics, ensuring efficient data integration, scalability, and real-time reporting for aerospace production processes
- Leveraged Docker and Kubernetes to containerize data analytics applications, ensuring efficient deployment and scalability of analytics solutions across production environments
- Conducted advanced data transformations and analytics using Apache Hive and Pig for processing and analysing unstructured data related to aerospace components and supply chain operations
- Worked with NoSQL databases such as MongoDB and Cassandra to handle unstructured data from IoT sensors and machine logs, improving predictive maintenance and production monitoring in the aerospace sector
- Howmet Aerospace is a global leader in the aerospace and defence industry, specializing in advanced materials and manufacturing technologies
- Environment: Power BI, Tableau, Looker, Informatica, Alteryx, Talend, machine learning, Python, R, Scikit-learn, SQL, PostgreSQL, Oracle, Teradata, AWS, Google Cloud Platform, Snowflake, AWS Redshift, Google Big Query, Python, Pandas, NumPy, Matplotlib, Seaborn, Hadoop, Apache Spark, Kafka, Docker, Kubernetes, Apache Hive, Pig, MongoDB, Cassandra
Senior Data Analyst
Comcast Corporation
Philadelphia, Pennsylvania
12.2023 - 03.2024
- Company Overview: Comcast Corporation is a global telecommunications and media conglomerate company is one of the largest broadcasters and cable television providers
- Prepared and presented the reports that summarize information and support business decisions and develop, implement, and maintain advanced analytics systems and Ensure data accuracy by performing data cleaning, validation, and quality checks
- Developed and maintained statistical models for predicting customer engagement and subscription patterns using Python and R, leveraging SQL, pandas, and NumPy for efficient data wrangling and analysis
- Created interactive dashboards and reports using Power BI and Tableau to track key performance indicators (KPIs), such as customer churn, sales performance, and service adoption, to provide real-time insights for business stakeholders
- Automated recurring data processes and reporting pipelines using SQL, Python scripts, and Apache Airflow, ensuring timely and accurate data delivery for marketing and sales teams
- Communicated insights and findings effectively through reports and presentations, utilizing Tableau and Power BI to visualize trends and support decision-making at the executive level
- Utilized ETL tools like Apache NiFi, Informatica, and SQL Server Integration Services (SSIS) to streamline data integration from multiple internal and external sources into Comcast's data ecosystem
- Managed large-scale data processing using Hadoop, enhancing data analysis capabilities by integrating Hive for fast querying and optimizing data retrieval for customer behaviour analysis
- Applied machine learning algorithms to optimize service delivery and personalize customer experiences, delivering actionable insights
- Leveraged Snowflake's cloud platform for scalable data warehousing and integrated with BI tools to enable real-time data analysis and reporting on customer and service metrics
- Utilized AWS services like S3, Redshift, and Athena for storing, processing, and analysing large-scale datasets to drive insights into customer usage patterns, content consumption, and performance metrics
- Designed and implemented data models and ETL pipelines to efficiently load structured and semi-structured data into Snowflake, facilitating comprehensive analytics and reporting capabilities across departments
- Developed custom visualizations using Matplotlib and Seaborn to identify key trends in content consumption, customer satisfaction, and service quality metrics, enabling actionable business insights
- Conducted advanced statistical analysis and hypothesis testing using SciPy and NumPy, optimizing customer segmentation models and improving targeted marketing strategies
- Comcast Corporation is a global telecommunications and media conglomerate company is one of the largest broadcasters and cable television providers
- Environment: SQL, Python, pandas, NumPy, Power BI, Tableau, QlikView, SQL, Python scripts, Apache Airflow, Power BI, Tableau, Apache NiFi, Informatica, Hadoop's, Hive, machine learning, Snowflake's, AWS Redshift, Athena, Power BI, Matplotlib, Seaborn, Snowflake
Data Analyst
Bajaj Allianz General Insurance
Hyderabad, India
12.2021 - 08.2023
- Company Overview: Bajaj Allianz General Insurance is a leading private general insurance company offers a wide range of insurance products, including motor, health, travel, home, and cyber insurance, catering to diverse customer needs
- I involved mapping risks, setting pricing, targeting prospects, tracking sales and service, analysing claims, detecting fraud and studying consumer behaviour
- Develop and maintain interactive dashboards and reports using tools like Power BI, Tableau, or Excel to present key performance indicators (KPIs) for insurance management
- Integrate data from multiple sources, including policies data, and claims, ensuring accuracy and consistency using SQL, Python, and ETL tools
- Conduct predictive modelling and statistical analysis to forecast patient outcomes, readmission rates, and insurance trends using R, Python, or SAS
- Manage large datasets and databases (e.g., MySQL, SQL Server, Oracle) to ensure timely and accurate data retrieval for decision-making
- Automate routine data reporting tasks and processes using SQL queries, Python, or PowerShell scripts to increase efficiency
- Use Excel to analyse and manipulate large datasets, create pivot tables, and develop charts and graphs to summarize insurance metrics, track performance, and generate reports for stakeholders
- Apply machine learning algorithms (e.g., regression, classification) using Python and scikit-learn to predict patient outcomes, optimize resource allocation, and identify trends in insurance data for improved decision-making
- Design and implement custom ETL pipelines using Informatica, Alteryx, or custom scripts to extract, transform, and load data from multiple insurance systems, ensuring seamless integration and efficient data processing for analysis
- Leverage Hadoop, Apache Spark, and Kafka to process and analyse large volumes of insurance data in real-time, enabling efficient data storage, stream processing, and advanced analytics for improved patient care and operational insights
- Develop interactive and dynamic dashboards using Power BI to visualize healthcare data, track key performance indicators (KPIs), and provide actionable insights for operational, and financial decision-making
- Bajaj Allianz General Insurance is a leading private general insurance company offers a wide range of insurance products, including motor, health, travel, home, and cyber insurance, catering to diverse customer needs
- Environment: Power BI, Tableau, Excel, SQL, Python, ETL, Python, SAS, SQL Server, Oracle, PowerShell, scikit-learn, Informatica, Alteryx, Hadoop, Apache Spark, Kafka, Snowflake
Data Analyst
Bank of Baroda
Hyderabad, India
06.2020 - 11.2021
- Company Overview: Bank of Baroda (BOB) is one of the largest and most well-established public sector banks in India
- Designed and created the easy-to-communicate and easy-to-understand graphic or visual representations of a large amount of complex quantitative and qualitative data and information with the help of static, dynamic or interactive visual items
- Develop and maintain data pipelines to extract, transform, and load (ETL) data from multiple sources into a centralized data warehouse
- Design and develop interactive dashboards and reports using tools like Tableau, Power BI, and Excel to communicate insights to non-technical stakeholders
- Leverage SQL, Python, and R for data manipulation, cleaning, and complex querying of large finance datasets
- Utilize machine learning models and statistical analysis techniques to predict future claims trends and cost drivers
- Provide support in creating and managing databases using MS SQL Server, Oracle, or cloud-based solutions (Azure)
- Build and maintain ETL pipelines using Apache Spark, Python, and SQL to ensure timely and accurate data delivery
- Create data visualizations using Tableau or Power BI to help stakeholders understand key trends and actionable insights
- Utilize Big Data technologies such as Hadoop and Apache Spark to process and analyse large volumes of customer data, ensuring scalability, efficiency, and real-time data processing for actionable insights
- Design and optimize data storage and processing workflows using Snowflake to ensure high-performance data retrieval, seamless integration with cloud platforms, and efficient handling of large-scale customer datasets
- Leverage scikit-learn, TensorFlow, and Kera’s to build and deploy machine learning models for predicting finance outcomes, identifying trends in claims data, and enhancing decision-making processes related to risk assessment and cost management
- Implement and manage data pipelines, storage solutions, and analytics workflows using Azure services such as Azure Data Factory, Azure SQL Database, and Azure Synapse Analytics to support efficient data integration, processing, and reporting in the finance domain
- Utilize Looker and Alteryx to create interactive dashboards and data visualizations, enabling stakeholders to explore customer data insights, track performance metrics
- Bank of Baroda (BOB) is one of the largest and most well-established public sector banks in India
- Environment: Tableau, Power BI, Excel, SQL, Python, machine learning, Apache Spark, Hadoop, Snowflake, scikit-learn, TensorFlow, Kera’s, Azure Data Factory, Azure SQL Database, Azure Synapse Analytics, Looker, Alteryx
Education
Masters - Business Analytics
Sacred heart university
Skills
- SAS
- SPSS
- VBA
- Power Query
- Tableau
- Alteryx
- Adobe Analytics
- Qlik Sense
- SharePoint
- SSRS
- Power BI
- Sisense
- JIRA
- Confluence
- Trello
- REST APIs
- GraphQL
- MATLAB
- RapidMiner
- KNIME
- Python
- Minitab
- Hadoop
- Spark
- Kafka
- Hive
- Looker
- Excel
- R
- SQL
- Pandas
- NumPy
- Matplotlib
- Seaborn
- SciPy
- Informatica
- Talend
- SSIS
- Snowflake
- AWS Redshift
- Google Big Query
- Regression
- Classification
- Clustering
- Time Series Forecasting
- MySQL
- PostgreSQL
- Oracle
- Microsoft SQL Server
- AWS
- Azure
- GCP
Timeline
Senior Data Analyst
Howmet Aerospace
04.2024 - Current
Senior Data Analyst
Comcast Corporation
12.2023 - 03.2024
Data Analyst
Bajaj Allianz General Insurance
12.2021 - 08.2023
Data Analyst
Bank of Baroda
06.2020 - 11.2021
Masters - Business Analytics
Sacred heart university
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