4+ years of proven expertise in Data Analysis, utilizing a diverse skill set encompassing statistical techniques, machine learning algorithms, and advanced data visualization tools. Led end-to-end SDLC projects, adeptly …
4+ years of proven expertise in Data Analysis, utilizing a diverse skill set encompassing statistical techniques, machine learning algorithms, and advanced data visualization tools. Led end-to-end SDLC projects, adeptly toggling between Agile and Waterfall, delivering Python, SQL, and R solutions for data analysis using NumPy, Pandas, Matplotlib, Seaborn, SciPy, ggplot2, and Scikit-learn. Excelled in data visualization with Tableau, Power BI, and Advanced Excel, integrating AWS services for scalable solutions across MySQL, SQL Server, PostgreSQL, MongoDB, and Oracle databases. Managed projects with Jira, HP Quality Center, and UAT, employing ETL tools, exploratory analysis, and statistical methods to extract actionable insights from diverse datasets. Applied SSIS, and SSRS for predictive modeling, classification, regression, clustering, and A/B testing, contributing to precise forecasting and modeling outcomes. Specialized in data cleaning, wrangling, storytelling, and association rule analysis, ensuring version control through Git and GitHub while excelling in KPI tracking and effective communication. Demonstrated adaptability in Windows, Linux, and Mac iOS environments, showcasing a comprehensive skill set in data analytics, statistics, data warehousing, and big data technologies. Worked closely with cross-functional teams, including Finance, Healthcare, and IT, to gather requirements and align data analytics with business goals, showcasing strong communication and problem-solving skills.
• Conducted SQL queries on Electronic Health Records (EHR) databases to extract specific patient information, including details from demographics tables, medical history records, medication databases, and discharge summaries.
• Implemented Extract, Transform, Load (ETL) processes to refine and structure raw healthcare data, ensuring its usability for further analysis.
• Executed Exploratory Data Analysis (EDA) techniques to gain insights into the distribution of patient demographics, diagnoses, and readmission rates. Utilized Python's Matplotlib and Seaborn libraries for visualizations, presenting key findings through detailed charts and graphs.
• Adhered to healthcare data regulations, particularly ensuring compliance with the Health Insurance Portability and Accountability Act (HIPAA) to protect patient privacy and confidentiality throughout the data extraction and analysis process.
• Leveraged visualization tools such as Tableau to connect to the cleaned and transformed healthcare dataset. Established connectors to seamlessly link Tableau to relevant databases containing patient information, facilitating direct access to up-to-date and accurate data for visualization and reporting purposes.
Conducted SQL queries on Electronic Health Records (EHR) databases to extract specific patient information, including details from demographics tables, medical history records, medication databases, and discharge summaries.
Implemented Extract, Transform, Load (ETL) processes to refine and structure raw healthcare data, ensuring its usability for further analysis.
Executed Exploratory Data Analysis (EDA) techniques to gain insights into the distribution of patient demographics, diagnoses, and readmission rates.
Utilized Python's Matplotlib and Seaborn libraries for visualizations, presenting key findings through detailed charts and graphs.
Adhered to healthcare data regulations, particularly ensuring compliance with the Health Insurance Portability and Accountability Act (HIPAA) to protect patient privacy and confidentiality throughout the data extraction and analysis process.
Leveraged visualization tools such as Tableau to connect to the cleaned and transformed healthcare dataset.
Established connectors to seamlessly link Tableau to relevant databases containing patient information, facilitating direct access to up-to-date and accurate data for visualization and reporting purposes.
Worked with Data Management team to analyze Reinsurance Data using tools like SQL, Access, Excel (Lookups, Pivot tables) and predicting any future impacts on business.
Pre-processed data for trading strategy evaluation using MySQL.
Consolidated data from separate tables into one table with a distinct symbol indicator for each stock, for easier evaluation of trading strategies.
Gathered customer data from various sources, including transaction logs, customer support interactions, and demographic information.
Utilized clustering algorithms such as k-means to segment customers based on purchasing behavior, frequency, and recency of interactions.
Presented A/B testing results in Tableau dashboards to compare the performance of different marketing strategies and utilized bar charts or box plots to showcase statistical significance and performance metrics.
Utilized ETL pipelines in Talend to implement customer segmentation algorithms and utilized components for clustering or classification to identify and assign customers to specific segments.
Developed a comprehensive UAT test plan outlining the testing scope, objectives, and acceptance criteria.
Leverage AWS EMR (Elastic MapReduce) for distributed computing when dealing with large-scale data processing tasks and implemented Spark or Hadoop on EMR for parallel processing.
Analyzed and extract data from various Confidential using SQL.
Performed data cleansing and manipulation by using excel VLOOKUP’s, pivot and other advance excel functions.
Captured end-to-end lineage and ensure proper impact analysis has been performed in the event of changes to data assets as they move across the pipelines.
Maintained data flow documentation and perform object mapping using BI tools and validation.
Participated in daily Agile and Scrum master meeting to provide feedback and updates on the project.
Used DAX functions to create measure and calculated fields to analyze data for logical visualization and used Power Queries to transform the data.
Created PowerPivot models and PowerPivot reports, publish reports onto SharePoint, and deploy models into SQL Server SSAS instance.
Extracted data from data warehouse server by developing complex SQL statements using stored-procedures and common table expressions (CTEs) to support report building.
Implemented report integration among Power BI, SSRS and Python reports.
نظام التوظيف التشغيلي المعتمد على الذكاء الاصطناعي أولاً، الذي يوحّد ويؤتمت دورة التوظيف بالكامل للمؤسسات الحديثة حول العالم.
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