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Samitha Singireddy - Data Analyst

samithasingireddy05@gmail.com

Location: Carlton, Minnesota, USA

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SENIOR DATA ANALYST SAMITHA SINGIREDDY +1(507)301-7307 Samithasingireddy05@gmail.com PROFESSIONAL SUMMARY: Possessing over 9 years of analytical experience, leveraging tools like SQL, Python, R,Excel, and Power BI across multiple industries. Expertise in SQL, Python, Power BI, Tableau, and cloud platforms (AWS, Azure, Databricks) to drive strategic insights. Skilled in developing predictive models using TensorFlow and PyTorch for customer behavior analysis. Strong background in ETL workflows, big data processing, and data governance to ensure accuracy and efficiency. Adept at automating data pipelines, improving efficiency by 40% in data processing. Experience in cloud-based data warehousing (AWS Redshift, Snowflake, Databricks) for scalable data solutions. Proficient in A/B testing, anomaly detection, and fraud analysis to enhance decision-making. Strong analytical and problem-solving skills with a focus on data-driven business strategies. Led cross-functional teams to implement BI dashboards and reports, improving executive decision- making. Hands-on experience with data mining, statistical modeling, and advanced analytics. Expert in customer segmentation, sales forecasting, and market trend analysis to optimize marketing strategies. Passionate about mentoring analysts, optimizing workflows, and driving process improvements. Experienced in data security, governance, and compliance best practices for cloud-based systems. Skilled in integrating data from multiple sources (APIs, databases, third-party tools) for enhanced analytics. Proven ability to translate complex data into actionable business insights, driving revenue growth and efficiency. Extensive experience in designing and deploying real-time reporting solutions using Power BI and Tableau. Adept at improving data accessibility and visualization for stakeholders across various business functions. Strong expertise in leveraging machine learning algorithms for process automation and predictive modeling. Experience working with high-volume datasets, ensuring accuracy, consistency, and efficient storage solutions. Ability to collaborate with cross-functional teams, including finance, IT, and marketing, to align data strategies with business objectives. Proven track record in reducing operational costs through data-driven insights and workflow optimizations. Expertise in Agile methodologies, ensuring timely delivery of projects through iterative development cycles. Strong understanding of business intelligence best practices, driving innovation through data-driven decision-making. Hands-on experience with natural language processing (NLP) for sentiment analysis and customer feedback evaluation. Knowledge of deep learning techniques for image and speech recognition applications. Experienced in developing recommendation systems to improve customer experience and engagement. TECHNICAL SKILLS: Skill Category Technologies/Tools Databases PostgreSQL, Microsoft SQL, Oracle, AWS Redshift Data Integration SSIS, Apache NiFi, Informatica, Oracle Data Integrator, Kafka Programming SQL, Python, R Data Visualization QlikView, Power BI, Tableau, Looker Machine Learning TensorFlow, PyTorch, Azure ML, Amazon SageMaker Cloud Platforms AWS (S3, QuickSight, Cloud), Microsoft Azure Cloud Data warehouse Snowflake Version Control Git Documentation SharePoint, Confluence Project Management Scrum, Agile Statistical Tools SPSS, MATLAB, Qualtrics API Integration RESTful API, FTP/SFTP Reporting Microsoft Excel, Adobe Analytics Business Intelligence Looker, LookML, dbt PROFESSIONAL EXPERIENCE: Client: Fifth Third Bank, Cincinnati, OH MAY2023-Present Role: Sr. Data Analyst Roles & Responsibilities: Developed data visualization dashboards in Power BI and Tableau for senior leadership decision- making. Conducted in-depth financial data analysis using SQL, providing insights that enhanced operational efficiency. Created machine learning models to predict credit risk and customer loan defaults. Implemented data pipeline automation using AWS Glue and Redshift, reducing processing time by 50%. Led company-wide adoption of SQL best practices, standardizing reporting procedures. Developed a real-time fraud detection system using anomaly detection algorithms. Optimized marketing campaign strategies through data-driven insights, increasing conversion rates by 15%. Conducted financial modeling to support investment and lending decisions. Managed large datasets in AWS S3, ensuring data integrity and accessibility. Built interactive reports to track business KPIs and present findings to key stakeholders. Designed customer segmentation models, enabling personalized financial products. Implemented predictive analytics for early detection of loan delinquencies. Spearheaded integration of third-party datasets to enhance business intelligence reporting. Improved reporting efficiency by developing automated SQL queries for scheduled reports. Provided training and mentorship to junior analysts on data analytics tools and methodologies. Developed API integrations to streamline data flow between internal and external financial systems. Created time-series forecasting models for risk assessment and credit portfolio management. Designed an executive-level dashboard to provide real-time performance tracking across departments. Implemented predictive analytics for early detection of loan delinquencies. Spearheaded integration of third-party datasets to enhance business intelligence reporting. Improved reporting efficiency by developing automated SQL queries for scheduled reports. Provided training and mentorship to junior analysts on data analytics tools and methodologies. Developed API integrations to streamline data flow between internal and external financial systems. Created time-series forecasting models for risk assessment and credit portfolio management. Designed an executive-level dashboard to provide real-time performance tracking across departments. Conducted exploratory data analysis (EDA) to identify potential revenue opportunities and cost savings. Led the migration of legacy data systems to cloud infrastructure, ensuring minimal downtime and data loss. Client: Voya, New York, NY Jul 2021 to Apr 2023 Role: Data Analyst Roles & Responsibilities: Conducted customer behavior analysis to enhance retention and engagement strategies. Built predictive models to forecast revenue trends, improving budgeting accuracy. Automated ETL pipelines using SQL and Python, increasing efficiency by 35%. Created real-time interactive dashboards using AWS QuickSight and Tableau. Optimized cloud data storage strategies, reducing infrastructure costs by 20%. Designed and implemented machine learning algorithms for risk assessment. Integrated multiple data sources to enhance CRM insights and targeted marketing campaigns. Conducted A/B testing to improve product offerings and pricing strategies. Provided strategic recommendations based on in-depth market and competitor analysis. Improved data accuracy by developing robust data validation processes. Analyzed financial performance metrics to optimize investment decision-making. Enhanced reporting automation, reducing manual processing time by 30%. Developed a customer churn prediction model using machine learning techniques. Collaborated with engineering teams to improve data infrastructure and governance. Designed and implemented Looker dashboards using LookML to enhance data accessibility and insights. Developed dbt models for structured and reusable data pipelines in Snowflake. Implemented SQL query optimizations that improved report execution speed. Designed KPI tracking dashboards for executive-level reporting, improving decision-making efficiency. Conducted deep-dive analysis on policyholder claims data to enhance fraud detection measures. Developed a recommendation engine to personalize financial product offerings based on customer data. Created automated workflows for real-time data integration from external financial sources. Led data governance initiatives to ensure compliance with financial regulations and industry standards. Conducted customer behavior analysis to enhance retention and engagement strategies. Built predictive models to forecast revenue trends, improving budgeting accuracy. Automated ETL pipelines using SQL and Python, increasing efficiency by 35%. Created real-time interactive dashboards using AWS QuickSight and Tableau. Optimized cloud data storage strategies, reducing infrastructure costs by 20%. Designed and implemented machine learning algorithms for risk assessment. Integrated multiple data sources to enhance CRM insights and targeted marketing campaigns. Conducted A/B testing to improve product offerings and pricing strategies. Provided strategic recommendations based on in-depth market and competitor analysis. Improved data accuracy by developing robust data validation processes. Analyzed financial performance metrics to optimize investment decision-making. Enhanced reporting automation, reducing manual processing time by 30%. Developed a customer churn prediction model using machine learning techniques. Collaborated with engineering teams to improve data infrastructure and governance. Implemented SQL query optimizations that improved report execution speed. Client: Express, Columbus, OH Dec 2019 to Jun 2021 Role: Data Mining Specialist Roles & Responsibilities: Conducted customer behavior analysis to enhance retention and engagement strategies. Built predictive models to forecast revenue trends, improving budgeting accuracy. Automated ETL pipelines using SQL and Python, increasing efficiency by 35%. Created real-time interactive dashboards using AWS QuickSight and Tableau. Optimized cloud data storage strategies, reducing infrastructure costs by 20%. Designed and implemented machine learning algorithms for risk assessment. Integrated multiple data sources to enhance CRM insights and targeted marketing campaigns. Conducted A/B testing to improve product offerings and pricing strategies. Provided strategic recommendations based on in-depth market and competitor analysis. Improved data accuracy by developing robust data validation processes. Analyzed financial performance metrics to optimize investment decision-making. Enhanced reporting automation, reducing manual processing time by 30%. Developed a customer churn prediction model using machine learning techniques. Collaborated with engineering teams to improve data infrastructure and governance. Implemented SQL query optimizations that improved report execution speed. Designed KPI tracking dashboards for executive-level reporting, improving decision-making efficiency. Conducted deep-dive analysis on policyholder claims data to enhance fraud detection measures. Developed a recommendation engine to personalize financial product offerings based on customer data. Created automated workflows for real-time data integration from external financial sources. Led data governance initiatives to ensure compliance with financial regulations and industry standards. Conducted customer behavior analysis to enhance retention and engagement strategies. Built predictive models to forecast revenue trends, improving budgeting accuracy. Automated ETL pipelines using SQL and Python, increasing efficiency by 35%. Created real-time interactive dashboards using AWS QuickSight and Tableau. Optimized cloud data storage strategies, reducing infrastructure costs by 20%. Designed and implemented machine learning algorithms for risk assessment. Integrated multiple data sources to enhance CRM insights and targeted marketing campaigns. Conducted A/B testing to improve product offerings and pricing strategies. Provided strategic recommendations based on in-depth market and competitor analysis. Improved data accuracy by developing robust data validation processes. Analyzed financial performance metrics to optimize investment decision-making. Enhanced reporting automation, reducing manual processing time by 30%. Developed a customer churn prediction model using machine learning techniques. Collaborated with engineering teams to improve data infrastructure and governance. Implemented SQL query optimizations that improved report execution speed. Client: Luxoft India Pvt. Ltd, India Oct 2017 to Sep 2019 Role: Database Analyst Roles& Responsibilities: Developed SQL queries and stored procedures to optimize database performance. Created interactive dashboards using QlikView and Power BI to visualize key business insights. Automated reporting workflows, reducing manual effort by 40%. Conducted statistical analysis using MATLAB and R for predictive modeling. Improved data validation processes, ensuring high accuracy in reporting. Assisted in the development of ETL pipelines for integrating disparate data sources. Led a team to optimize data retrieval processes, reducing query execution times. Conducted deep-dive analysis on customer transaction data to uncover insights. Implemented security best practices for data handling, ensuring compliance with industry regulations. Developed Python scripts for data preprocessing, improving efficiency in analytics workflows. Designed scalable ETL processes to manage large datasets across various business units. Developed Power BI and Tableau dashboards to monitor key operational metrics. Integrated Kafka and Apache Spark for real-time data ingestion and analysis. Automated routine data extraction and transformation tasks using Python. Built machine learning models to detect anomalies in financial transactions. Led the migration of database infrastructure from on-premise to cloud-based solutions. Provided technical documentation and training for SQL best practices and reporting standards. Client: Inautix Technologies India Pvt Ltd, India Jan 2016 to Sep 2017 Role: Data analyst Roles & Responsibilities: Developed SQL queries for data retrieval from PostgreSQL databases, focusing on optimizing performance and accuracy. Utilized Microsoft Excel for advanced data manipulation and analysis, applying complex formulas to enhance data insights. Created visualizations in QlikView to illustrate data trends, aiding in the interpretation and presentation of results. Implemented Apache Hadoop for large-scale data processing, managing and analyzing big data effectively. Utilized Spark for real-time data analysis and processing, enhancing the speed and efficiency of data operations. Managed version control with Git to track and revert changes effectively, maintaining project integrity. Created detailed documentation for all data-related processes, using Microsoft Excel and Word to ensure clarity and accessibility. Developed Power BI dashboards to display key performance indicators, improving organizational decision-making processes. Conducted routine reports to support business decision-making, employing SQL and Excel to deliver timely insights. Trained new employees on data tools and best practices, enhancing team capabilities and ensuring consistent quality. Collaborated with IT to ensure system compatibility and security, focusing on data integrity and protection. Optimized data storage solutions to enhance system performance and reduce costs, applying best practices in database management. Monitored data quality and implemented corrections as necessary, using tools like SQL and Excel to maintain high standards. Conducted data analytics to support project implementation phases, leveraging tools like SQL and Power BI for comprehensive analysis. Education: Bachelor of Technology (B.Tech) in Computer science and Engineering, SRM Institute of Technology & sciences Keywords: machine learning business intelligence sthree rlang information technology New York Ohio