Data Analyst

SUMMARY

AELURI SUCHARITHA

Data Analyst

Kansas, USA +1-913-***-**** ****************@*****.*** LinkedIn Data professional with 4 years of experience in data engineering and analytics while transforming complex datasets into actionable insights across Healthcare, IT, Finance, and E-commerce. Skilled in data modeling, statistical analysis, and machine learning, leveraging Python, R, SQL, and Scala to drive data-driven decision-making. Experienced in building interactive dashboards with Tableau, Power BI, and Looker to communicate insights effectively. Expertise in ETL (Extract, Transform, Load) processes, data cleaning, and automation techniques to improve data accuracy and efficiency. Strong background in cloud platforms (AWS, GCP, Azure, Snowflake), and database management (SQL Server, PostgreSQL, MySQL, Oracle). Experience with Excel functions such as Power Query, pivot tables, VLOOKUP, INDEX MATCH, and macros for automation and reporting. Adept at applying statistical methods, including regression analysis and hypothesis testing, to identify patterns and optimize performance. Strong foundation in data privacy regulations (HIPAA, HITECH Act) and compliance standards. Passionate about optimizing business operations, improving forecasting accuracy, and enhancing strategic decision-making through advanced analytics. SKILLS

Data Analysis: Data Wrangling, Data Cleaning, Data Modelling, Data Mining, Predictive Analytics, Statistical Analysis, Time Series Analysis, Cluster Analysis, Anomaly Detection, Data Segmentation Programming & Query Languages: Python (Pandas, NumPy, Scikit-learn), R, SQL (MySQL, PostgreSQL, SQL Server, Oracle), Scala Data Visualization: Tableau, Power BI, Looker, Matplotlib, Seaborn, ggplot2 Reporting & BI: Power Pivot, Microsoft Excel

Data Engineering & ETL: Apache Spark, Databricks, Apache Airflow, Alteryx, Snowflake, Hadoop, Data Warehousing, SSIS Machine Learning & AI: Scikit-learn, TensorFlow, Keras Database Management: MySQL, SQL Server, PostgreSQL, MongoDB, Oracle Big Data & Cloud Platforms: AWS (S3, Redshift, Glue, Lambda), GCP(Google Cloud Platform), Azure Methodologies: SDLC, Agile, Scrum, Lean Startup, DevOps Analytics Automation: Docker, Kubernetes, CI/CD (GitHub Actions, Jenkins) Compliance & Security: Data Privacy Regulations (HIPAA, HITECH Act), GDPR EXPERIENCE

Capital One Financial - USA

Data Analyst July 2024 - Present

• Developed and deployed financial models using Python libraries (PyCaret, TensorFlow), improving fraud detection accuracy by 30% and reducing false positives by 25%.

• Automated ETL workflows using Alteryx, SQL, and Apache Airflow, reducing data processing time by 40% and minimizing manual intervention in financial reporting.

• Integrated financial data extraction from Snowflake and Redshift using Python & SQL, cutting manual efforts by 30%.

• Utilized Databricks on AWS to process and optimize high-volume financial transactions, improving data pipeline efficiency.

• Designed and implemented interactive Power BI and Looker dashboards, leading to a 20% improvement in financial forecasting accuracy and a 15% reduction in reporting errors.

• Used real-time data ingestion with Apache Kafka, ensuring up-to-date insights for investment and risk analysis.

• Implemented data governance frameworks using tools like Collibra to enhance data cataloging, lineage, and compliance adherence across financial datasets.

• Applied blockchain technology for secure transaction analysis and compliance tracking, ensuring transparency in financial operations. CitiusTech -India

Data Analyst Nov 2019 - December 2022

• Implemented predictive analytics and time series models, increasing forecasting accuracy for patient readmission rates by 25%, leading to better resource allocation in hospitals.

• Designed and deployed serverless ETL pipelines on AWS Glue, reducing processing time by 40%.

• Optimized SQL queries to handle large-scale data more efficiently, resulting in a 30% decrease in database response times and increasing overall data processing speed, and used VLOOKUP and advanced Excel functions(Macros, VBA) to analyze survey data on public safety power shutoffs in various counties, identifying trends and patterns.

• Optimized Redshift and Snowflake queries, reducing report generation time from 20 minutes to 5 minutes.

• Collaborated with IT, clinical, and business teams to integrate Electronic Health Records (EHR) and Health Information Systems (HIS), ensuring seamless data flow and the accuracy of reports for healthcare initiatives.

• Ensured strict compliance with HIPAA and HITECH Act healthcare data privacy regulations, mitigating risks and maintaining the confidentiality of sensitive healthcare data.

• Automated repetitive tasks using CI/CD pipelines with Jenkins and Git, improving efficiency, and ensuring the consistent delivery of updates to dashboards and reports.

• Built real-time dashboards in Tableau and Power BI that reduced manual reporting time by 50%, improving executive decision-making speed and efficiency.

• Collaborated with cross-functional teams to elicit, analyze, and document business requirements using Agile methodologies such as Scrum and Kanban.

• Conducted A/B testing on various healthcare data models to measure the effectiveness of predictive analytics, leading to a 15% improvement in model accuracy.

PROJECTS

Deep Semantic Analysis on Restaurant Feedback Using NLP

• Developed LSTM and FFNN models for sentiment analysis and topic modeling on restaurant reviews.

• Collected and pre-processed data from Yelp, TripAdvisor, and social media using CountVectorizer.

• Achieved high accuracy and F1 score, with LSTM outperforming FFNN in capturing sentiment nuances.

• Designed interactive visualizations (word clouds, sentiment heatmaps) for actionable insights. Enhancing Movie Recommendation Systems Using Machine Learning

• Built a personalized recommendation system using Support Vector Machines (SVM), Decision Trees, and Random Forest.

• Processed and analyzed user viewing history, ratings, and reviews using Python (Pandas, NumPy), Scikit-learn, and NLP techniques.

• Implemented collaborative & content-based filtering, improving precision and recall.

• Optimized models with feature engineering and hyperparameter tuning (GridSearchCV).

• Compared multiple ML models, achieving 82% accuracy with SVM. EDUCATION

University of Central Missouri Warrensburg, Missouri January 2023 - May 2024 Masters in computer science

TKR College of Engineering and Technology, Hyderabad, India August 2017 – July 2021 Bachelor of Technology in Computer Science

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