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Data Analyst | 7+years | Austin, TX | Open to relocate - Data Analyst

[email protected]

Location: Austin, Texas, USA

Relocation: Yes

Visa: H1B

Resume file: Chaitanya - Data Analyst_1768580380750.docx Please check the file(s) for viruses. Files are checked manually and then made available for download.

Professional Summary: With over 7 years of experience in Data Analysis and Business Intelligence, with a focus on leveraging tools like Tableau, Power BI, Alteryx, SQL, SAS and Python to drive data-driven decision-making and optimize business processes across diverse industries, including retail, telecommunications, and healthcare. Proven track record of developing and maintaining automated reporting solutions that have led to significant reductions in manual reporting time, increased operational efficiency, and empowered stakeholders to make faster, more accurate data-driven decisions. Integrated SAS with BI tools like Tableau and Alteryx to enhance data pipelines, automate reporting, and support the development of interactive dashboards, reducing manual reporting time and improving data accuracy. Expertise in building dynamic, interactive dashboards and visualizations that provide real-time insights into key performance metrics, enabling senior management and cross-functional teams to make informed decisions quickly and effectively. Highly proficient in designing and implementing optimized SQL queries for data extraction, transformation, and reporting, resulting in improved query performance and reduced processing time by up to 30%, ensuring timely access to critical business data. Extensive experience in utilizing Alteryx to automate ETL processes, streamline data extraction, transformation, and loading procedures, reducing manual intervention by up to 50%, and enhancing the overall data pipeline efficiency. Expertise in developing predictive models using Python and R to forecast critical business metrics such as demand, customer churn, and inventory levels, allowing businesses to implement proactive strategies and mitigate risks before they occur. Led cross-functional collaboration efforts with marketing, sales, supply chain, IT, and senior leadership teams to ensure that reporting and analytical solutions are aligned with broader business goals, ultimately driving the company s strategic objectives. Demonstrated ability to manage large datasets, perform detailed exploratory analysis, and uncover meaningful insights that directly contributed to business outcomes such as increased customer retention, improved sales, and better market segmentation. Extensive experience in using SAS for statistical analysis, data manipulation, and reporting, enabling deep insights into customer behavior, product performance, and operational metrics that guided strategic business decisions. Delivered high-impact insights into customer behavior, product performance, and market trends, which enabled targeted business strategies and helped maximize ROI on marketing campaigns, improving campaign performance by up to 15%. Successfully led data integration initiatives by merging disparate data sources and ensuring consistency and accuracy across systems, improving data availability and reporting efficiency by 30%, and enhancing the overall quality of insights. Developed and implemented data governance frameworks to promote best practices in data accuracy, consistency, and quality, ensuring stakeholders had reliable, standardized data to guide strategic business decisions. Designed and implemented advanced forecasting models that improved inventory management accuracy, reduced overstock by 18% and optimized stock levels for better demand alignment, helping to reduce waste and improve customer satisfaction. Proficient in leveraging SAS procedures (PROC SQL, PROC MEANS, PROC FREQ, PROC REG) for exploratory data analysis, segmentation, and forecasting, contributing to improvements in marketing ROI and sales forecasting accuracy. Applied advanced statistical and cohort analysis techniques to uncover insights from customer data, improving targeting strategies, segmentation, and marketing personalization, which led to higher conversion rates and increased customer acquisition. Managed the migration of legacy data systems to modern BI platforms, such as Power BI and Tableau, ensuring a seamless transition while improving reporting capabilities, cutting down the time to generate insights by 35%, and enhancing user experience. Utilized SAS and led the design and implementation of predictive models for demand forecasting, inventory planning, and customer retention, supporting proactive decision-making and driving operational efficiency across retail and telecom sectors. Conducted A/B testing for pricing strategies and promotional campaigns, providing actionable insights that directly influenced marketing decisions, resulting in a 12% improvement in campaign effectiveness and increased sales conversion rates. Designed automated reporting solutions to enhance service performance tracking, enabling leadership teams to monitor and improve customer experience, directly contributing to a 12% increase in customer satisfaction in telecom and retail industries. Education: Master of Science, Business Analytics & Project Management, University of Connecticut, Hartford B.Tech. Electronics and Communication Engineering, NRI Institute of Technology, India Certification: Microsoft Certified Azure Fundamentals (AZ 900) Tableau Certified Desktop Specialist (TDS - C01) Technical Skills: Analysis Tools: Tableau, TIBCO Spotfire, Power BI, SAS, MS SSRS, MS Excel (VBA, VLOOKUP, Pivot tables) Data Integration (ETL) Tools: Alteryx, Pipeline Pilot, Informatica, MS SQL Server Integrated Service (SSIS) Project Management: SDLC - Waterfall & Agile methodologies, project life cycle, MS Project 2013, JIRA Programming: SQL, PL/SQL, Python, R-Script, C#, CSS, HTML, JavaScript, jQuery Application Software: MS Office, Eclipse, MATLAB, Visual Studio, MS Excel advance, MS Access, MS Visio, Toad Oracle Operating System: Windows Server, Windows Server, Windows NT / XP and Windows Linux, UNIX Database Tools: SQL Plus, SQL Loader, SQL Developer, Python, TOAD, Teradata, ETL, Data Stage/Quality Stage Professional Experience: Client: Menards, Eau Claire, Wisconsin Mar 2023 to till date Role: Sr. Data Analyst Responsibilities: Led comprehensive data analysis for sales and inventory departments, identifying trends and inefficiencies, resulting in a 15% reduction in inventory costs and 20% improvement in sales cycle efficiency across multiple business units. Developed and maintained automated reporting solutions using Tableau, reducing manual report generation time by 40%, enabling stakeholders to make timely, data-driven decisions. Collaborated with the supply chain team to design SQL queries for product movement, improving stock level accuracy and reducing stockouts by 25% during peak sales periods. Designed and implemented Alteryx workflows to automate the ETL processes, reducing manual data processing time by 50% and improving reporting efficiency. Utilized advanced data visualization techniques to provide senior leadership with real-time insights into sales performance and inventory turnover, enabling better decision-making and faster market reactions. Conducted detailed exploratory analysis of customer purchasing patterns, identifying opportunities for targeted marketing and optimizing pricing strategies. Created predictive models using R and Python to forecast seasonal demand with 95% accuracy, aligning inventory levels. Partnered with IT and data engineering teams to optimize SQL queries and data pipelines, ensuring efficient reporting systems. Utilized SAS for statistical analysis and data manipulation on large sales and inventory datasets, uncovering actionable trends that led to a 15% decrease in inventory costs and improved supply chain efficiency. Developed dynamic dashboards to visualize product performance across regions, enabling regional managers to optimize sales and inventory. Coordinated the development of a data governance framework, ensuring data accuracy and consistency in reporting, and training 30+ stakeholders to promote data standards. Collaborated with the marketing department to analyze promotional campaigns, refining strategies, and leading to a 12% increase in campaign ROI. Leveraged SAS procedures (PROC SQL, PROC MEANS, PROC FREQ) to conduct detailed customer segmentation and purchasing behavior analysis, contributing to a 12% boost in targeted campaign ROI. Developed complex data models and reporting tools to support operational decision-making, providing timely insights into sales trends, inventory turnover, and product profitability. Played a key role in optimizing demand forecasting models, integrating historical sales and external market data, improving forecast accuracy, and enabling better inventory planning. Trained and mentored junior analysts, fostering collaboration and enhancing the team's data analytics capability through Tableau, Alteryx, and SQL. Worked with stakeholders to convert business acceptance criteria into Gherkin-based BDD test cases, ensuring clear traceability from requirements to test logic. Collaborated with cross-functional teams, including merchandising, supply chain, and IT, ensuring reporting and analytical solutions met business needs and aligned with strategic objectives. Leveraged advanced SQL skills to design complex queries and reports for tracking product sales, customer demographics, and market trends, providing actionable insights for business planning. Designed and implemented an advanced inventory tracking system using Alteryx workflows, enabling efficient stock management and improving reporting accuracy by 25%. Used Azure DevOps (ADO) to document test cases, track user stories, link them to commits and pipelines, and streamline agile workflows. Implemented A/B testing methodologies to analyze customer response to promotions and pricing strategies, providing data-driven insights that influenced pricing decisions. Developed reusable data transformation logic that aligned with Gherkin-defined acceptance rules, reducing testing rework and increasing QA automation efficiency. Participated in business review meetings, providing stakeholders with in-depth analyses and visualizations on performance metrics, helping leadership evaluate current trends. Migrated legacy SAS reports to modern BI platforms (Power BI, Tableau), ensuring consistency and accuracy while reducing manual reporting overhead by 35%. Client: Charter communications, Stamford, Connecticut Jan 2022 to Feb 2023 Role: Data Analyst Responsibilities: Conducted deep data analysis to enhance customer service operations, identifying inefficiencies and uncovering trends that led to a 20% reduction in customer response times and improved service delivery. Developed and maintained Tableau dashboards to track service performance metrics, providing real-time insights to senior leadership, helping the company respond proactively to service issues. Integrated SAS with Tableau dashboards to enhance reporting on promotional effectiveness and product performance, providing end users with deeper, statistically driven insights. Designed and optimized SQL queries for extracting and analyzing customer behavioral data, reducing query processing time by 25%, enhancing decision-making speed and accuracy. Created predictive models using Python and R to forecast customer churn risk, leading to the implementation of retention strategies that reduced attrition by 15%, improving customer loyalty. Automated ETL processes using Informatica, streamlining data extraction, transformation, and loading procedures, reducing manual reporting efforts by 30% and ensuring stakeholders had timely, accurate information. Collaborated with QA and data engineering teams to align BDD (Behavior-Driven Development) testing with business logic validation. Led data integration of external customer datasets, improving data availability and reporting efficiency by 20%, ensuring a more comprehensive data set for analysis. Developed and deployed data-driven solutions to enhance customer experience, analyzing pain points and optimizing touchpoints, increasing customer satisfaction by 12%. Designed and maintained automated reporting tools for forecasting sales trends and revenue projections, improving forecasting accuracy by 25%, and aiding in future growth planning. Collaborated closely with the product team to analyze customer feedback and improve product features, driving product adoption rates up by 8%. Collaborated with the data science team to operationalize predictive models in R and SAS for forecasting seasonal demand, improving forecast precision and minimizing overstock by 18%. Led A/B tests marketing initiatives, analyzing customer response to pricing strategies and promotions, improving campaign effectiveness by 12% and boosting conversion rates. Delivered reports on service usage patterns to identify trends in customer behavior, helping management make informed decisions and contributing to a 10% increase in customer retention. Worked with business stakeholders to translate complex findings into actionable insights, directly contributing to improved sales performance by optimizing customer retention strategies. Documented test coverage and acceptance criteria using Gherkin syntax, supporting cross-functional alignment between analysts, developers, and testers. Designed and deployed business intelligence reports to monitor key operational metrics, reducing manual reporting time by 40% and increasing reporting accuracy. Analyzed marketing campaign effectiveness, delivering data-driven insights that resulted in a 15% increase in ROI and optimized future strategies. Implemented real-time dashboards to monitor service performance and customer satisfaction, providing stakeholders with instant access to critical metrics and enabling faster decision-making. Conducted analysis of customer service quality, identifying areas for improvement, which led to the introduction of strategies that reduced customer complaints by 10%. Provided actionable insights into customer demographics, tailoring marketing strategies and product offerings, leading to a 5% increase in new customer acquisitions. Collaborated with cross-functional teams to design scalable data solutions, improving reporting capabilities and reducing data retrieval times by 20%. Client: ESN Technologies, India Nov 2018 to Jun 2021 Role: Business Data Analyst Responsibilities: Conducted comprehensive data analysis on logistics and delivery routes, identifying inefficiencies and opportunities for optimization, leading to a 10% reduction in delivery time across key regions. Developed and maintained Power BI dashboards for real-time tracking of delivery metrics, providing senior management with key insights to improve operational performance and decision-making. Collaborated with the operations team to design and implement SQL queries for analyzing shipment data, ensuring accuracy and completeness in delivery tracking and reporting. Created predictive models using Python to forecast peak delivery periods, allowing the company to allocate resources efficiently and reduce delays during high-demand seasons. Automated data extraction and reporting processes using Alteryx, cutting manual report generation time by 40% and enabling faster data-driven decisions for the operations team. Developed complex SQL queries to analyze customer delivery data, uncovering trends in delivery frequency and customer satisfaction, which helped improve customer retention strategies. Provided actionable insights into delivery route optimization, working with the logistics team to reduce fuel costs by 12% by optimizing delivery paths and reducing unnecessary stops. Created and maintained a centralized database for tracking key performance indicators (KPIs) such as on- time delivery rates, package volumes, and customer satisfaction metrics. Worked closely with cross-functional teams, including supply chain, marketing, and IT, to ensure seamless integration of data systems and enhance overall data accessibility and reporting efficiency. Designed and implemented dynamic reporting tools using Power BI and SQL, allowing business units to access real-time performance reports and making it easier to track and optimize operational efficiency. Conducted A/B testing for different delivery strategies and promotional offers, providing insights that led to a 15% increase in customer satisfaction and loyalty. Created automated dashboards in Power BI to monitor delivery team performance and identify bottlenecks, allowing managers to make real-time adjustments and improve team productivity. Performed detailed analysis of customer feedback data, identifying key pain points in the delivery experience and recommending process improvements that enhanced customer service. Collaborated with the IT team to improve the accuracy and reliability of data pipelines, ensuring that delivery data was clean, up-to-date, and ready for analysis in a timely manner. Analyzed seasonal trends in shipping volumes, helping the operations team plan and allocating resources more effectively to ensure timely deliveries during peak periods. Provided regular ad-hoc reporting and analysis on key operational metrics to senior leadership, helping drive strategic decisions around resource allocation and delivery strategy. Utilized advanced SQL techniques to optimize database queries, reducing the time to retrieve key operational reports by 20%, thus improving the efficiency of decision-making. Implemented a data-driven approach to monitor and improve delivery times, using data analytics to identify and address root causes of delays. Led the migration of legacy data systems to modern BI platforms, ensuring that the transition was smooth and resulted in improved reporting capabilities and data accessibility across teams. Client: Focus SoftNet, India May 2017 to Oct 2018 Role: Data Analyst/Tableau Developer Responsibilities: Analyzed patient data to identify trends in healthcare utilization and patient outcomes, providing actionable insights to improve service delivery and patient care. Developed and maintained SQL queries to extract, transform, and load (ETL) healthcare data, ensuring accurate reporting and compliance with regulatory standards. Created and optimized Tableau dashboards to visualize key healthcare metrics, such as patient admission rates, treatment outcomes, and resource utilization, providing real-time insights for senior management. Collaborated with clinical teams to develop predictive models using R and Python, forecasting patient admission trends and improving capacity planning. Conducted detailed data profiling to ensure the quality and accuracy of patient records, identifying discrepancies and recommending data validation measures to enhance data integrity. Worked with healthcare stakeholders to design and implement A/B tests for patient engagement strategies, resulting in a 10% increase in patient satisfaction and retention. Developed data models to predict patient outcomes based on historical medical data, contributing to more personalized treatment plans and better clinical decision-making. Utilized Alteryx workflows to automate data extraction, transformation, and loading processes, reduce manual data handling time by 30% and improve reporting accuracy. Generated routine reports on healthcare operational metrics, such as patient wait times and emergency room visits, providing leadership with insights to optimize hospital operations. Collaborated with IT teams to integrate external healthcare data sources, improving the comprehensiveness of data analytics and enabling more accurate reporting of patient trends. Performed cohort analysis on patient demographics and treatment outcomes, identifying high-risk patient populations and recommending interventions to reduce readmission rates by 12%. Worked closely with healthcare compliance teams to ensure that all data processing and reporting adhered to HIPAA and other relevant healthcare regulations, ensuring data privacy and security. Developed and implemented predictive analytics models to optimize resource allocation, such as staffing levels and medical equipment usage, reducing inefficiencies and operational costs. Created customized dashboards in Tableau to monitor real-time healthcare operations, providing stakeholders with instant access to data on patient care, financials, and resource utilization. Conducted ad-hoc analysis on healthcare data to support decision-making in areas such as patient scheduling, treatment protocol optimization, and cost reduction strategies. Collaborated with clinical researchers to analyze medical research data, uncovering new insights that supported evidence-based practices and improved clinical trial outcomes. Developed automated reporting systems that tracked key performance indicators (KPIs) in patient care, helping hospitals meet quality benchmarks and improve patient outcomes. Utilized statistical techniques to analyze healthcare claims data, identifying patterns in claims denials and recommending process improvements to reduce administrative costs. Built and maintained databases for patient and provider data, ensuring seamless data flow across departments and improving access to essential healthcare information for operational teams. Presented actionable insights to senior leadership, including recommendations on patient care strategies, cost-saving measures, and performance improvements based on detailed data analysis. Keywords: csharp quality analyst business intelligence active directory rlang information technology microsoft mississippi procedural language Arizona