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Click here or scroll down to respond to this candidate Candidate's Name
Data Analyst
PHONE NUMBER AVAILABLE | EMAIL AVAILABLE | Chicago, IL| LinkedIn | GitHub
Summary
Around 4 years of experience in Data Analysis, Data Validation, Data Modeling, Data Profiling, Data Verification, Data Mapping,
Data Loading, and Data Warehousing testing.
Proficient in Python for developing custom scripts and automating tasks, skilled in SQL for complex queries and database
management; experienced in R for statistical analysis and predictive modeling.
Expertise in SQL, including writing SQL Queries, Dynamic-queries, sub-queries, and complex joins for generating Stored Procedures,
Triggers, Functions, Views, and Cursors.
Proficient in Python, utilizing Pandas and NumPy for data manipulation, cleaning, transformation, and visualization.
Strong foundation in statistical analysis, predictive modeling, machine learning, data mining, quantitative analytics, multivariate
testing, and optimization algorithms.
Proficient in AWS services (EC2, S3, Lambda, and EMR) for data storage, computation, and analysis.
Active participation in all SDLC stages, emphasizing agile development. Regularly engaged in SCRUM meetings.
Skilled in Data Migration, Cleansing, Transformation, Integration, & Import/Export via ETL tools like Informatica Power Center.
Proficient in data validation and writing SQL statements (Stored Procedures, Functions, Triggers, packages).
Crafted diverse Tableau visualizations: Bar, Line, Pie charts, Maps, Scatter Plots, Heat maps, Table reports.
Experienced in Text Analytics, Python data visualizations, and Power BI dashboard creation for insights from unstructured data.
Technical Skills
Programming Languages: Python, R, SQL, Shell Scripting, SAS, STATA,
Databases: Relational(MySQL, SQL Server, PostgreSQL), NoSQL (MongoDB, Cassandra)
Big Data Tools: Apache Kafka, Spark, Apache NiFi, Airflow, Hadoop, Hive, SSIS
Data Visualization Skills: Tableau, Power BI, AWS Quick sight, Matplotlib, Seaborn, Plotly, SSRS
Data warehousing: Snowflake, Amazon Redshift, Google Big Query
Analytical Skills: Data Mining, Data Cleansing, Statistical Analysis, Data Visualization, Text Mining, ETL
Machine learning skills: Scikit-learn, Decision Trees, Random Forest, Predictive Modeling, Regression, Classification,
Clustering and Time Series Analysis.
Others: AWS ( EC2, S3, Lambda),Git, Docker, MS Excel (Formulas, Pivot tables, Lookups)
Education
M.S. in Computer Science - Illinois Institute of Technology, Chicago IL Aug 2021 - May 2023
B.S. in ECE - Gitam University, Visakhapatnam, India Jun 2014 - Apr 2018
Experience
Data Analyst - BCBS, IL Aug 2023 - Present
Crafted Power BI dashboards illustrating critical healthcare Key Performance Indicators (KPIs), enhancing comprehension by 30%
among 50+ executives.
Employed Power BI to develop insightful visuals demonstrating healthcare program adherence, analyzing a substantial 3TB of data,
resulting in a 20% increase in crucial operational decisions.
Implemented standardized SQL Server data validation checks via Python scripts, reducing dirty data by 70% and promoting data
consistency.
Achieved over 10% reduction in healthcare expenses during seasonal peaks and enhanced equipment longevity by introducing A/B
testing frameworks for medical devices.
Utilized clustering algorithms to extract trends and patterns from patient data, enabling personalized treatment methodologies and
delivering 25% better health outcomes.
Generated SSRS reports linked with normalized Oracle DB, aggregating data from various sources to establish a single source of truth
for patient metrics.
Developed a scalable cloud ETL pipeline on Azure, leveraging Azure Virtual Machines and Azure Functions to migrate 2TB of legacy
healthcare data into a Snowflake data warehouse in under 3 hours.
Analyzed 1.5 million patient records using SQL queries, identifying medication inconsistencies and potential risks. This analysis,
showcased on a Clinical Dashboard, led to a 30% reduction in diagnostic errors, saving the hospital over $11.5 million annually by
avoiding liabilities and unnecessary procedures.
Leveraged Python and its powerful libraries (NumPy, Pandas, SciKit-Learn, Matplotlib, Seaborn, Plotly, PySpark, and NLTK) to
analyze complex datasets.
Actively engaged in agile practices, gaining valuable insights into project management and ensuring a 15% acceleration in healthcare
project deliveries during the analysis phase.
Produced 120 insightful capacity planning visuals, optimizing resource allocation processes. Leveraged Power BI to design
visualizations ranging from Pie Charts to Scatter Plots, enhancing stakeholder clarity and driving data-driven decisions.
Managed and optimized storage solutions on Azure, utilizing Azure Blob Storage for storing unstructured data and Azure SQL
Database for structured data.
Data Analyst Accenture, India Jul 2018 - Jan 2021
Developed a Stakeholder Mapping dashboard in Tableau to optimize NBN Co's engagement, collaborating across departments for
strategic alignment with RSPs, government agencies, local communities, wholesale customers, and technology providers.
Monitored NBN's performance using internal portals, identified high-demand areas, and proactively addressed congestion issues,
showcasing adept problem-solving skills.
Collaborated with network engineers, designers, Database Developers, and Data Engineers, leveraging tools like Microsoft Teams,
PowerPoint, Microsoft Word, Gmail, and NBN's portals for effective communication and collaboration.
Utilized Matplotlib to create a wide range of visualizations including line plots, bar charts, histograms, scatter plots, and heatmaps to
effectively communicate insights from data analysis.
Participated in the development and management of a scalable data warehouse using Hive, improving data storage and accessibility
by 40%, thereby enhancing data-driven decision-making processes.
Collaborated on accurate data collection, cleansing, and organization for 50,000+ Australian locations using Excel.
Maintained detailed documentation of Python scripts and data analysis methods, reducing new team member onboarding time by
20% and ensuring analysis replicability.
Assisted in designing and implementing advanced SQL data models, optimizing data organization for a 15% increase in insights.
Collaborated on the development of Chabots and virtual assistants using NLP frameworks.
Assisted in the seamless integration of MySQL with diverse data sources, reducing data silos by 30% and facilitating streamlined data
consolidation, analysis, and reporting.
Contributed to the application of time series forecasting techniques, resulting in a 15% reduction in inventory costs through optimized
inventory management and resource allocation.
Contributed to creating solution-driven Power BI views and dashboards, using diverse chart types for effective data presentation.
Supported performance optimization for Power BI reports, achieving a 40% reduction in load times, and implementing robust data
governance policies to ensure data accuracy and compliance.
Implemented text mining to extract entities, relationships, and concepts from text data for deeper insights.
Data Analyst - KPMG, India Sep 2017 - Jun 2018
Utilized Python to perform exploratory data analysis (EDA) on large datasets, utilizing libraries such as Pandas for data manipulation
and NumPy for numerical computations.
Conducted thorough data gathering and reconciliation using Excel, leading to a 20% increase in data accuracy and reliability.
Developed custom scripts and workflows to automate repetitive tasks, improving efficiency and accuracy of data processing.
Managed and maintained Oracle databases to ensure data availability and reliability. Monitored database performance, conducted
regular backups, and implemented disaster recovery procedures to minimize downtime and data loss.
Crafted advanced SQL queries for in-depth analysis and reporting, focusing on aggregation, grouping, and filtering.
Applied NumPy for efficient numerical computing and data manipulation tasks. Used NumPy arrays and functions to perform
mathematical operations, manipulate large datasets, and handle missing or invalid data.
Ensured data integrity and security within the PostgreSQL database. Implemented access controls, encryption, and data validation
procedures to protect sensitive data from unauthorized access and corruption.
Performed data aggregation, grouping, and filtering operations with Pandas. Used Pandas Data Frames to manipulate and analyze
tabular data, applying functions to group data, aggregate values, and filter rows based on specific criteria.
Created Pivot Charts from PivotTable data to enhance data visualization and communication of trends and patterns.
Developed interactive dashboards and reports in Power BI to visualize data insights, providing stakeholders with interactive tools to
explore data trends and patterns.
Implemented data refresh schedules in Power BI to maintain data accuracy and consistency.
Employed AWS Athena for querying complex datasets, achieving a 40% reduction in query execution time.
Implemented AWS Lambda functions for automated data quality checks, reducing data-related errors by 70%.
Conducted comprehensive data profiling and data mining to identify trends, patterns, and outliers, contributing valuable insights to
business strategy development.
Performed advanced time series analysis to forecast future trends and drive proactive business strategies.
Projects
YouTube Data Analysis
Tech Stack: AWS S3, AWS Glue, Quick Sight, AWS Lambda, AWS Athena, AWS IAM, SQL, Python3
Analyzed video metrics for UK and Canada channels, using Python functions, automated Lambda triggers, AWS Glue Studio ETL jobs,
and efficient S3 data management, yielding deep insights into video analytic and engagement.
Retail Analytics using Walmart Dataset
Tech Stack: SQL, Bash, AWS EC2, Docker, MySQL, Sqoop, Hive, and HDFS
Demonstrated strong analytical skills in uncovering crucial store sales insights, utilizing retail analytics proficiency with Walmart data
for informed decision-making; adept in end-to-end data pipeline management from acquisition to analysis.
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