Summary
Overview
Work History
Education
Skills
AI ML Experience and Projects
Languages
Personal Information
Timeline
Generic

Akanksha Dhall

Faridabad

Summary

Accomplished QA Lead with a proven track record at UKG, enhancing operational efficiency and employee satisfaction through expert application of Selenium with JAVA and Agile methodologies. Spearheaded cross-functional teams, driving a 30% improvement in project delivery timelines. Renowned for exceptional problem-solving and team management skills, adept at fostering client relationships and advancing technological solutions.

Overview

10
10
years of professional experience

Work History

QA LEAD

UKG
06.2022 - Current
  • Product Overview: Workforce Management solutions streamline critical activities such as time tracking and scheduling, reducing administrative burdens on managers and employees. These solutions are designed to strike the perfect balance—maximizing productivity while also inspiring and motivating employees. By optimizing workflows and improving resource allocation, Workforce Management empowers organizations to achieve operational efficiency and enhance employee satisfaction.
  • Requirement Gathering and Analysis: Collaborated with teams to gather and document requirements on Confluence, and developed detailed test plans, strategies, scenarios, scripts, and steps based on Business and System Use Cases.
  • Testing and Automation: Performed functional testing with Selenium WebDriver in a Hybrid-driven and BDD framework, automated web application testing, and conducted manual and API testing. Assisted developers with troubleshooting and performed Root Cause Analysis (RCA) for defects
  • Scrum Participation: Actively participated in scrum meetings and project reviews, ensuring team alignment and progress tracking, while supporting the creation and maintenance of Requirement Traceability Matrices (RTMs).
  • Client Relationship and Communication: Led and participated in client discussions to ensure alignment with project requirements, tracked and reported issue progress, and suggested resolutions.
  • System and Team Management: Analyzed existing systems for improvements, managed a team of technicians and inspectors to ensure adherence to requirements, and demonstrated strong multitasking skills while handling multiple deliveries and meeting deadlines.
  • DevOps and Infrastructure: Maintained Jenkins pipelines for continuous integration and deployment, and used Docker and Kubernetes to create and manage virtualized environments for development and testing.

Consultant -B2

Capgemini/Altran
08.2019 - 06.2022
  • Product Overview: Central Access and Administrative Services (CAAS) refers to a set of centralized services designed to manage access control, administrative functions, and overall security across an organization's IT systems and resources. These services streamline the management of user permissions, authentication, and administrative tasks, providing greater efficiency, security, and compliance.
  • Client Interaction & Requirement Analysis: Gathered and analyzed business requirements across teams, documenting findings in Confluence and JIRA. Collaborated with stakeholders to create Requirement Traceability Matrices (RTMs) for alignment with project goals, and conducted impact analysis while providing inputs for risk assessment and project timelines.
  • Test Planning, Strategy & Execution: Developed test plans, strategies, and cases based on business requirements and performed various testing types including functional, regression, integration, UAT, and cross-browser testing. Automated tests using Selenium, TestNG, Cucumber, and RestAssured, and conducted mobile testing with Appium. Reported defects via JIRA, Bugzilla, and HP ALM, ensuring timely resolution.
  • Agile Collaboration & Scrum: Actively participated in Agile ceremonies, including stand-ups, sprint planning, backlog grooming, and retrospectives.
  • Test Reporting & Analysis: Generated test execution reports and defect metrics using tools like TestRail, Zephyr, and Excel.
    Provided detailed test summary reports to stakeholders, highlighting test coverage, defects found, and resolutions.
  • Leadership & Delivery Management: Managed teams across multiple deliverables, ensuring adherence to timelines and high-quality standards. Mentored junior QA engineers and coordinated with cross-functional teams for successful project execution. Demonstrated strong task prioritization skills while managing multiple projects under tight deadlines.

Engineer-2/Quality

Iomedia
Gurgaon
11.2017 - 08.2019

Product Overview: Ticketmaster is a global platform for purchasing tickets to live events like concerts, sports, and theater. It offers event discovery, ticket sales, and event management services, with features such as mobile ticketing, real-time inventory tracking, and personalized recommendations. Ticketmaster simplifies access to events for consumers worldwide.

Automation Framework & Test Case Development: Designed, created, and maintained automation frameworks, automating test cases to enhance testing efficiency and coverage.

Requirements Evaluation & Test Plan Design: Evaluated project requirements and specifications to identify user/customer needs, and designed detailed test plans in TestRail based on those requirements.

Collaboration & Project Delivery: Collaborated with cross-functional teams to ensure quality across multichannel experiences and contributed to delivering brand-centric solutions in a full-service marketing agency.

Associate Consultant QA

Oodles Technologies
Gurgaon
09.2016 - 10.2017
  • Product Overview: LiveSource is the first end-to-end supplier portal created to manage the launch process. It ensures all departments and stakeholders are working with the latest, up-to-date information.
  • Test Script Fixes and New Test Cases: Actively worked on debugging and improving existing test scripts while also writing new test cases to ensure robust coverage of application functionalities.
  • Jenkins Builds: Responsible for checking the Jenkins builds to verify that the continuous integration process runs smoothly, identifying issues early in the deployment pipeline.
  • Bug Reporting: Actively reported bugs with detailed descriptions, categorizing them under appropriate headings for efficient tracking and resolution by the development team.

Assistant Professor

Lingayas University
Faridabad
01.2015 - 09.2016
  • Assistant professor in the Electronics and Communication department
  • Worked on internal IT projects: Responsible for Quality Assurance (QA). Conducted testing, identified defects, and ensured alignment with project requirements. Collaborated with cross-functional teams to maintain high-quality standards and contribute to successful project delivery.
  • Mentored Students: Mentored and assisted with student-centered activities on campus to establish professional relationships.

Education

PG Program - Machine Learning and AI

Great Lakes Institute of Management
01.2014

M.tech - VLSI

Amity University
Noida
01.2014

B.tech - EC

BBSCET (GBTU)
Allahabad
01.2011

12th -

UP BOARD
Lucknow
01.2007

10th -

UP BOARD
Lucknow
01.2005

Skills

  • Selenium with JAVA
  • X-path
  • GIT
  • Tortoise SVN
  • POM
  • Hybrid model framework
  • JIRA
  • RCA of bugs
  • Agile
  • Mac
  • Windows
  • Linux
  • VM Ware
  • CI-CD Pipeline
  • API Testing
  • Postman
  • Graphical (AWS inbuilt tool)
  • Cucumber
  • BDD
  • TestNG
  • Testrail
  • Zephyrs
  • Smoke testing
  • Sanity testing
  • Functional testing
  • Integration testing
  • Acceptance testing
  • Release testing
  • API Rest Assured framework
  • Database testing
  • Test planning
  • Test cases creation
  • Execution
  • Dashboard Creation
  • Machine learning skills
  • Python
  • Panda
  • Supervised Algorithms
  • Unsupervised learning algorithms
  • Data Preprocessing
  • Data Manipulation
  • Data Reporting tool
  • Tableau
  • Power BI
  • Neural Network
  • LLM
  • Natural Language Processing (NLP)

AI ML Experience and Projects

Data Processing & Visualization: Expert in data preprocessing techniques, including handling missing values, duplicates, outliers, and imbalanced datasets. Proficient in feature scaling, feature engineering, and data normalization. Skilled in using Python, Java, TensorFlow, SQL, and data visualization tools like Tableau and Power BI. Experienced in using Matplotlib and Seaborn for univariate, bivariate, and multivariate analysis.
Machine Learning Algorithms & Statistical Methods: Proficient in supervised algorithms like Logistic Regression, Decision Trees, Random Forest, SVM, k-NN, and Naive Bayes for classification and regression tasks. Experienced in ensemble learning methods like Random Forest, Gradient Boosting, AdaBoost, and Bagging. Skilled in unsupervised learning using K-Means and PCA. Strong background in statistical methods, including probability theory, regression analysis, ANOVA, Bayesian statistics, time series analysis, and cluster analysis.
Model Deployment & NLP: Experienced in deploying machine learning models using Flask. Knowledgeable in Neural Networks, LLMs, and recommendation systems. Strong skills in NLP techniques such as Transformers, Hugging Face, GloVe, and vectorization. Familiar with Git and Jenkins for version control and CI/CD processes.

Applied Statistics Project: Utilized plotting distribution, visualization, and hypothesis testing to analyze industry problems and make data-driven decisions across various domains.

Supervised Learning Project: Applied popular classification techniques and extensive EDA to predict patient conditions and customer conversion for focused marketing.

Ensemble Techniques Project: Developed a machine learning model to predict customer churn for a telecommunications company, enhancing customer retention.

Unsupervised Learning Project: Implemented clustering and classification techniques to segment cars based on fuel consumption and classify vehicles from silhouettes.

Feature Engineering & Model Tuning: Used supervised learning and ensemble techniques to predict yield outcomes in semiconductor manufacturing, optimizing process efficiency.

Neural Networks & Deep Learning: Delivered two sub-projects, including a regressor/classifier for equipment signal quality prediction and an image classifier for street-level number

Languages

  • English
  • Hindi

Personal Information

Date of Birth: 07/13/91

Timeline

QA LEAD

UKG
06.2022 - Current

Consultant -B2

Capgemini/Altran
08.2019 - 06.2022

Engineer-2/Quality

Iomedia
11.2017 - 08.2019

Associate Consultant QA

Oodles Technologies
09.2016 - 10.2017

Assistant Professor

Lingayas University
01.2015 - 09.2016

PG Program - Machine Learning and AI

Great Lakes Institute of Management

M.tech - VLSI

Amity University

B.tech - EC

BBSCET (GBTU)

12th -

UP BOARD

10th -

UP BOARD
Akanksha Dhall