Data Analyst Power Bi

Ayeshabi Tigdikar Data Analyst

Location: MA Mobile: 203-***-**** Email: **.********@*****.*** LinkedIn SUMMARY:

Experienced Data Analyst with 4.5+ years of experience in healthcare, telecommunications, and pharmaceutical sectors. Skilled in SQL, Python, R, and data visualization tools such as Tableau and Power BI. Experienced in analysing healthcare claims, creating predictive models, and designing interactive dashboards to support data-driven decision-making. Proficient in ETL processes, statistical modelling, and cloud technologies, delivering impactful results by leveraging advanced data analytics solutions. SKILLS

Programming Languages: Python, SQL, R, C, HTML, CSS, JavaScript Python Libraries: Pandas, NumPy, Scikit-learn, Matplotlib, Seaborn, StatsModel, TensorFlow, Keras Databases: MySQL, MS SQL Server, Oracle, Google BigQuery, MongoDB Data Visualization Tableau, Power BI, ggplot2

ETL Tools: SQL Server Integration Services (SSIS), Alteryx, Snowflake, Power Query Cloud Technologies: AWS (EC2, S3, RDS, Sage Maker), Google Cloud Platform (GCP) Statistical Analysis: ANOVA, T-tests, Regression Models, PCA, A/B Testing Tools: JIRA, Confluence, Git, MS Excel, VBA, Hadoop, Spark, Splunk EXPERIENCE

CVS Pharmacy, USA April 2024 – Present

Data Analyst

• Analyzed large-scale healthcare datasets to identify trends and patterns, improving operational efficiency by 25% and enhancing patient outcomes.

• Designed and deployed interactive Tableau and Power BI dashboards for real-time KPI tracking and strategic decision-making.

• Developed ETL workflows using SQL and Python, centralizing multi-source data into a single repository, reducing manual processes by 30%.

• Conducted A/B testing using R and Python to improve healthcare email campaign efficiency and optimize patient outreach.

• Engineered automated processes for healthcare claims data validation, ensuring data accuracy and reducing discrepancies by 25%.

• Leveraged advanced machine learning models, including Random Forest and Logistic Regression, to forecast healthcare utilization with 15% greater accuracy.

Vodafone PLC, India Aug 2020 – Aug 2022

Data Analyst

• Designed 15+ interactive Tableau dashboards to track financial metrics, pricing elasticity, and sales performance, enabling data- driven strategies.

• Automated data workflows using SQL, Dataiku, and Spark SQL, resulting in a 20% increase in data processing efficiency.

• Integrated Google BigQuery with GCP-based ETL pipelines for real-time analytics, improving data accuracy by 50%.

• Collaborated with Agile teams, conducting daily scrums and managing project workflows using JIRA and Confluence.

• Conducted clustering analyses and predictive modeling to identify pricing trends, directly improving profit margins by 10%. Philips Healthcare, India Aug 2018 – Jul 2020

Data Analyst

• Analyzed complex healthcare datasets, supporting product development and improving operational decision-making.

• Utilized R and Python for statistical analyses, including hypothesis testing, trend analysis, and time series forecasting.

• Created data validation protocols, reducing errors by 20% and ensuring accurate insights for strategic planning.

• Developed insightful visualizations using ggplot2 and Seaborn, enabling effective communication of key data insights.

• Optimized database queries and ETL processes to streamline data pipelines and improve analysis efficiency. EDUCATION

Master of Science in Project Management (Analytics) May 2024 Northeastern University, MA

Bachelors in Information Technology May 2020

COEP Technological University, India

PROJECTS

Comparative Analysis of Apple Watch and Fitbit Tracking Accuracy (2024)

• Conducted a comprehensive analysis using Tableau to evaluate the accuracy of health and fitness metrics tracked by Apple Watch and Fitbit.

• Utilized statistical methods to compare performance across various metrics, ultimately demonstrating that the Apple Watch outperformed Fitbit by 15% in accuracy.

• Presented findings to stakeholders, providing actionable insights to inform product development and marketing strategies. Pharmacy Claims Data Warehousing Project (2024)

• Led an extensive pharmaceutical data analysis project focused on optimizing claims data management and reporting efficiency.

• Executed SQL-based normalization processes to achieve Third Normal Form (3NF) and developed a star schema to facilitate efficient querying and reporting.

• Resulted in a 30% improvement in query performance, enhancing data accessibility for stakeholders and supporting timely decision-making in pharmacy operations.

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