👑𝗦𝗼𝗳𝘁𝘄𝗮𝗿𝗲 𝗔𝘂𝘁𝗼𝗺𝗮𝘁𝗶𝗼𝗻 𝗤𝘂𝗮𝗹𝗶𝘁𝘆 𝗘𝗻𝗴𝗶𝗻𝗲𝗲𝗿
✅Web applications • Desktop applications • Mobile apps
✅Banking • Insurance • Healthcare • Travel • E-commerce • Education
▶️ Core Expertise
✅ Manual Testing, Functional testing , System testing, Integration Testing, Usability Testing, Cross browser testing, Smoke testing, Re-testing, Regression Testing, UAT, Database Testing, black box testing, Negative testing, Sanity, and Exploratory testing.
✅ Strong experience in Requirement analysis, provide Test estimation, Test Planning, Test case/script designing in and QC, Microsoft excel, Test artifacts review, Requirement Traceability Matrix, Test Execution, Defects logging, and Reporting.
✅Sound work experience in SDLC, STLC, Testing processes & methodologies.
✅Experience in waterfall model, V-model, Scrum and Agile methodology
✅Preparation of daily/weekly status reports and follow ups on bug fixes and builds.
✅Defined and implemented the Defect management processes and activities.
✅Experience in bug triage – analyzing, prioritizing, and scheduling.
✅Superior analytical and troubleshooting skills, excellent communication and presentation skills, passionate about quality.
✅Test management tools : Microsoft excel, QC 9.0/9.2, ALM , Mercury Test Director
✅Defect Tracking tools : Jira, Clear Quest, Clearcase, Teamtrack, MS excel, MS Word, Notepad
✅Databases : MS SQL Server , DB2, Oracle, Sybase
✅Languages : SQL, C, Java
✅Networks : HTTP, HTTPS, TCP/IP, FTP
✅Operating Systems : Windows XP, 2000, 98
✅Version Control : Microsoft Visual SourceSafe, SVN, Git
✅Browser : Edge, Firefox, Chrome, Safari
I am an entry-level data analyst with a passion for turning raw data into valuable insights. I have a strong foundation in data analysis techniques, statistical analysis, and data visualization. With a keen eye for detail and a problem-solving mindset, I am dedicated to helping businesses make data-driven decisions.
✅ Data Analysis: Proficient in analyzing large datasets using tools like Python or SQL. Skilled in data cleansing, data transformation, and data manipulation techniques to derive meaningful insights.
✅ Statistical Analysis: Familiar with statistical concepts such as hypothesis testing, regression analysis, and correlation analysis. Capable of using statistical software (e.g., SPSS, SAS) to perform statistical modelling.
✅Data Visualization: Experienced in creating visually appealing and informative charts, graphs, and dashboards using tools like Tableau, Power BI, or Excel. Able to present complex data concisely and understandably.
✅Data Mining: Knowledgeable in extracting relevant information from structured and unstructured data sources using techniques like web scraping or text mining. Proficient in using tools such as BeautifulSoup or Scrapy.
✅Problem-Solving: Strong analytical and critical thinking skills to identify patterns, trends, and outliers in data. Ability to translate business questions into analytical problems and develop actionable recommendations.
✅Reporting and Presentation: Effective communication skills to present analysis findings through comprehensive reports and engaging presentations. Able to tailor the information to different audiences and explain complex concepts clearly and concisely.
✅Data Management: Understanding of database concepts and experience with data management systems like MySQL or PostgreSQL. Competent in data querying and database design.
✅Excel: Proficient in utilizing Excel for data analysis tasks, including data cleaning, sorting, filtering, and creating formulas and pivot tables. Familiarity with advanced Excel functions (e.g., VLOOKUP, INDEX-MATCH).