Data Science Specialist with 6+ Years Experience

Vijaya Chowta

Email id: *************@*****.*** phone no: 201-***-****.

PROFESSIONAL SUMMARY

● Hands on experience in Data analysis and Data visualization using Matplotlib/Seaborn

● Strong understanding of advanced Tableau features like calculated fields, table calculations, joins, data blending and dashboard actions.

● DataBase development in MYSQL. Developed data layer for the application. Designed data schemas and designed data flow architecture. Intelligence tools and application of Statistical Concepts.

● Proficient in Predictive Modeling, Data Mining Methods, Factor Analysis, ANOVA, Hypothetical testing, normal distribution, and other advanced statistical techniques.

● Developed predictive models using Decision Tree, Random Forest, Naïve Bayes, Logistic Regression, Cluster Analysis, and Neural Networks.

● Experienced in Python to manipulate data for data loading and extraction and worked with python libraries like Matplotlib, Numpy, Scipy and Pandas for data analysis.

● Worked with data mining tools such as Matlab to develop neural network, cluster analysis.

● Expertise in transforming business requirements into analytical models, designing algorithms, building models, developing data mining and reporting solutions that scales across massive volumes of structured and unstructured data.

● Developed various machine learning models such as Logistic regression, KNN, and Gradient Boosting with Pandas, NumPy, Seaborn, Matplotlib, Scikit-learn in Python.

● Experience in building production quality and large-scale deployment of applications related to natural language processing and machine learning algorithms.

● Exposure to AI and Deep learning platforms such as TensorFlow, Keras, AWS ML.

● Proficient in Tableau data visualization tools to analyze and obtain insights into large datasets, create visually powerful and actionable interactive reports and dashboards..

● Skilled in using statistical methods including exploratory data analysis, regression analysis, regularized linear models, time-series analysis, cluster analysis, goodness of fit, Monte Carlo simulation, sampling, cross-validation, ANOVA.

● Generated data visualizations using tools such as Tableau, Python Matplotlib, Python Seaborn.

● Extensive experience in Text Analytics, developing different Statistical Machine Learning, Data Mining solutions to various business problems and generating data visualizations using Python.

● Proven ability to manage all stages of project development Strong Problem Solving and Analytical skills and abilities to make Balanced and Independent Decisions

● Sorted data into MS-Excel to facilitate management and exporting. Good MS-Excel skills like VLOOKUP, Pivot-tables. Strong understanding on creating parameters and sets use them in parameter actions.

● Experience handling Customer requests and working with them in the Iterative process and fulfilling their needs. Experience in presentation frameworks such as MS PowerPoint.

● Proficient in the entire project life cycle and actively involved in all the phases including data extraction, data cleaning, statistical modeling and data visualization with large data sets of structured and unstructured data.

● Used new Tableau features Viz in ToolTip, Cross Database joins on existing reports.

● Extensive experience interacting with Department Managers and different levels of users and developers. Ability to communicate business and technical issues to both business users and technical users.

PROFESSIONAL EXPERIENCE:

Data Quality Analyst Lead at MICHAEL KORS November2024-March2026 Key Responsibilities:

● Performed comprehensive manual functional Regression Testing across multiple releases to ensure system stability and prevent production defects.

● Executed end-to-end (E2E) order placement testing, validating complete order lifecycle including cart, checkout, payment processing, order confirmation, and backend order management.

● Conducted order processing validation, including refunds, cancellations, pricing validation, tax calculations, and fulfillment flow verification via NARVAR portal.

● Performed analytics testing by validating tracking events, data layer variables, and ensuring accurate data capture across user journeys.

● Executed pixel testing (e.g., marketing and conversion pixels) to validate firing conditions, event triggers, and data accuracy using browser developer tools and network logs

● Tested and validated GDB (Global Digital Backlog) releases, ensuring new features and bug fixes met functional and non-functional requirements before production deployment.

● Designed, developed, and implemented automation scripts in TOSCA, converting manual test cases into reusable automated test scripts to improve regression efficiency.

● Implemented the Order placing flow in TOSCA to reduce the effort to perform E2E order placement and validation

● Created and maintained detailed test cases, test plans, and defect reports using structured documentation standards via JIRA and everything is documented in Confluence Pages.

● Collaborated closely with developers, business analysts, and product teams to clarify requirements and resolve defects efficiently.

Environment: Jira, Qtest, Confluence, SFCC BM, MAO, WMi, Tricentis TOSCA. Data Scientist at LeadXpression Feb2019 – Oct2024

Key Responsibilities:

● Involved in gathering, analyzing, and documenting business requirements, functional requirements, and data specifications.

● Working with Business Analysts to gather dashboard requirements for development.

● Interact with business users on a daily basis to gather requirements and demo the dashboards and presentations.

● Built and tested different Ensemble Models such as Boosted aggregating, Bagged Decision Trees and Random Forest, Gradient boosting, to improve accuracy, reduce variance and bias, and improve stability of a model

● Coordinated with the ETL and DB team to create the denormalized tables and views needed for development.

● Used tableau joins to connect to multiple tables in DB2 and created an extract to work with.

● Developed a dashboard with five reports mainly driven by the heatmap and used the dashboard filter action to filter other reports on the dashboard.

● Created crosstab with calculated fields to show current escalation count vs. prior period selection.

● Expertise in transforming business requirements into analytical models, designing algorithms, building models, developing data mining and reporting solutions that scales across massive volumes of structured and unstructured data.

● Involved in the entire data science project life cycle and actively involved in all the phases including data extraction, data cleaning, statistical modeling and data visualization with large data sets of structured and unstructured data.

● Experienced in Python to manipulate data for data loading and extraction and worked with python libraries like Matplotlib, Numpy, Scipy and Pandas for data analysis.

● Developed trend charts to show escalation count trends for the selected employee/report.

● Created parameters and set actions and created period type calendar.

● Skilled in using statistical methods including (EDA) exploratory data analysis, regression analysis, regularized linear models, time-series analysis, cluster analysis, goodness of fit, sampling, cross-validation, ANOVA.

● Proven ability to manage all stages of project development Strong Problem Solving and Analytical skills and abilities to make Balanced and Independent Decisions

● Built and tested different Ensemble Models such as Boosted aggregating, Bagged Decision Trees and Random Forest, Gradient boosting, to improve accuracy, reduce variance and bias, and improve stability of a model

● Generated Heat maps to identify the risk and flaws in the business.

● Expertise in creating show/hide sheets on dashboard and other formatting with containers and navigation buttons.

● Give demo/briefings to clients as and when development is complete. Environment: Python, Matplotlib, Seaborn, pandas, Numpy, Tableau 2020.1, MySQL Participated in Online certification Programs – Earned a reward certificate. Language Prediction using Machine Learning (NLP)

● Created a language prediction model by leveraging Python and pandas for data manipulation and analysis.

● Employed CountVectorizer to convert text data into numerical features for machine learning algorithms.

● Encountered difficulties in accurately identifying languages with similar linguistic patterns.

● Resolved language prediction issues by fine-tuning model hyperparameters and optimizing feature extraction methods.

Data Analyst at WebClick Media Dec 2016 - Jan 2019 Key Responsibilities:

● Involved in gathering, analyzing data from Portfolio Finance Business Users and transforming data to Tableau Visualizations.

● Involved in the study of user requirements, analysis & review of designs and schema.

● System documentation, program specification and testing.

● Work with a variety of Databases (Relational, Flat Files, In-Memory) to create reports using Tableau.

● Perform Data mining, cleansing and preparing the data for Advanced Analytics.

● Develop and deliver reports, dashboards and visualizations.

● Publish, maintain and schedule the reports dashboards in matplotlib,Seaborn as Python libraries.

● Interact with business users on a daily basis to gather requirements and demo the dashboards and presentations.

● Audit datasets and data analysis as required ensuring their continuity, accuracy and consistency.

● Built and tested different Ensemble Models such as Boosted aggregating, Bagged Decision Trees and Random Forest, Gradient boosting, to improve accuracy, reduce variance and bias, and improve stability of a model

● Generated Heat maps to identify the risk and flaws in the business.

● Tackled highly imbalanced Fraud dataset using sampling techniques like under sampling and oversampling with SMOTE (Synthetic Minority Over-Sampling Technique) using Python Scikit-learn.

● Utilized PCA and other feature engineering techniques to reduce the high dimensional data, applied feature scaling, handled categorical attributes using one hot encoder of scikit-learn library.

● Developed various machine learning models such as Logistic regression, KNN, and Gradient Boosting with Pandas, NumPy, Seaborn, Matplotlib, Scikit-learn in Python.

● Do code reviews, project planning, backlog grooming, implementing, resolving issues to align with the Agile Process followed by the team.

● Suggest solutions and perform POC's to integrate and widen tableau's usability

● To maintain professional links with project clients as directed by the manager, particularly with regard to the collection and analysis of their data, including responding to ad hoc queries or requests, and to gain an understanding of their needs.

● To deliver internal reports/presentations to staff to obtain collaborative feedback into the product output.

● Create develop special ad-hoc reports, database queries, status reports, Daily Reports etc. as requested by Business Users and management

● Maintain Enhance current Dashboard reports.

● Complete visualizations for assigned activities and publish them to Tableau server.

● Assisting users with questions and issues using Tableau.

● Collecting data on various process measurements and formatting them into graphs using Tableau.

Environment: Python, Matplotlib, Seaborn, pandas, Numpy, Tableau 2020.1, MySQL

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