Experienced Quality Assurance Analyst with a 2-year tenure at eUnison Healthopedia LLP, overseeing end-to-end development and testing processes for the "DocHub" healthcare app. Adept at formulating and executing test strategies, collaborating with stakeholders, and ensuring adherence to Agile Scrum methodologies. Proven track record in identifying and resolving application issues, optimizing project timelines, and contributing to innovative testing processes. Skilled in effective communication, proactive problem-solving, and quick adaptation to new technologies. Open to relocation for the right opportunity.
• Orchestrated collaboration with clients and project teams to grasp intricate requirements, meticulously testing the functionalities of the "DocHub" healthcare app.
• Crafted a tailor-made test strategy, meticulously aligning it with the unique blend of business and system requirements to safeguard project timelines without compromising on quality.
• Formulated exhaustive test scenarios and scripts, delving into application functionalities and end-to-end integrations. • Executed rigorous functional testing, system testing, regression testing (integrating automation), and end-to-end testing to validate the robustness of the application.
• Engaged actively in customer calls, dynamic requirement gathering sessions, and sprint planning/grooming sessions, ensuring seamless integration of testing activities into the agile development process.
• Maintained a symbiotic relationship with clients and project teams, fostering effective communication channels throughout the testing lifecycle.
• Engineered a robust test strategy and approach, harmonizing with the unique demands of the application under test and upholding the integrity of project timelines.
• Spearheaded test planning activities for each sprint, ensuring meticulous execution in line with the defined test strategy.
• Innovatively identified and implemented technical innovations, elevating the value proposition and efficiency of the testing processes while continuously contributing fresh perspectives to enhance overall testing effectiveness.
• Demonstrated a proactive and self-initiated approach, efficiently resolving challenges with limited supervision, showcasing agility in quickly mastering new testing tools and technologies.
• Applied regression analysis, including linear regression and time series modeling, to forecast future energy consumption trends leveraging diverse data sources like smart devices, utility meters, and infrastructure projects.
• Presented analytical findings and recommendations through visually compelling dashboards and reports, using tools like Tableau and Power BI, enabling clients and internal stakeholders to make strategic decisions based on comprehensive data analysis.
• Utilized statistical models to derive data-driven insights, enabling informed decision-making for clients across Middle Eastern, African, and Indian territories in matters pertaining to energy efficiency strategies and sustainable solutions.
Understanding, Test Planning, Strategy Definition, Formulation, Functional Testing, Regression Testing, Automation, Collaboration, Communication, Innovation, Continuous Improvement, Learning Agility, Self-Motivation, Proactive, TeamworkPython, R, SQL, DBMS and DW: Tableau, Power BI, Oracle Applications, MS Project, SAP BO Analysis, SAP Predictive Analytics, SAS, Azure, Data Modeling, UML Diagrams, ETL Tools (SSIS), Google Analytics, JIRA, Visio, Teradata, MS Excel
Analytical Skills, Problem Solving, Project Management, Communication Skills, Requirement Gathering, Learning Agility, Negotiation Skills, Teamwork, Customer-Centric Approach, Stakeholder Management
• Conducted rigorous data cleansing using Python to enhance the quality and i integrity of the dataset for subsequent linear regression modeling.
• Engineered and trained a linear regression model on 80% of the dataset, employing advanced statistical techniques to predict house prices with precision.
• Attained a notable accuracy rate of 91% by rigorously testing the model on the remaining 20% of the dataset, demonstrating the reliability and effectiveness of the developed predictive model.
• Transformed US wildfires data with 1.8 million rows to 3NF using ER diagram and loaded the MySQL database.
• Evaluated the top causes, intensity, damage, and location for wildfires across the nation using MySQL