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Click here or scroll down to respond to this candidateCandidate's Name
Phoenix, AZ 85023 PHONE NUMBER AVAILABLE EMAIL AVAILABLE Candidate's Name Professional SummaryDynamic analytics professional with a proven track record at Grand Canyon University, enhancing credit risk management with an 81.7% accuracy predictive model. Detail-focused Data Science Analyst with knowledge in Machine Learning and data analytics. Ability to understand customer requirements and translate these into actionable project plans. SkillsProgramming/Visualization:Python (Anaconda, Numpy, Pandas, SK-learn, Matplotlib), Power Bi, Tableau, Microsoft Excel(VBA, Pivot tables), CRM, R, SQLAlgorithms:Linear Regression, Random Forest, Decision Tree, Gradient Boosting, Logistic Regression, kNN, SVM's, MLP, Natural Language Processing, Unsupervised learning (PCA, Clustering, Text analysis), Time Series AnalysisProfessional:Skilled in administrative and project management, collaboration and teamwork, innovative problem-solvingWork HistoryBenchmark Capstone Project Predictive Analytics 05/2024 to 07/2024 Grand Canyon University Phoenix, AZ Led and developed a predictive analytics model to identify potential credit card defaulters, leveraging historical transaction data, customer demographics, and payment histories. Utilized machine learning algorithms such as Random Forest, Logistic Regression, and Boosted Decision Tree to enhance credit risk management, achieving an accuracy of 81.7%. Employed Synthetic Minority Oversampling Technique (SMOTE) to handle class imbalance and improve model recall, ensuring that minority classes like defaulters were not overlooked. Conducted exploratory data analysis (EDA) to uncover patterns in default behavior, highlighting the influence of variables such as age, marital status, and education level on repayment risk. Ensured data quality through techniques like multivariate analysis, one hot encoding, and feature scaling, improving the reliability and predictive power of the model. Deployed the Two-factor Boosted Decision Tree model, outperforming other models with a precision of 75.6% and AUC of 0.785, effectively minimizing financial risks for the bank. Implemented an iterative tuning process and cross-validation for model evaluation, ensuring robust performance and scalable deployment across the bank's branches.STEM Student Worker Analyst 05/2023 to 07/2024Grand Canyon University Phoenix, AZ Organized and executed STEM events for high school students, fostering interest in data science and technology, resulting in a 20% increase in student engagement. Assisted in the 2024 GenCyber Teacher Camp Machine Learning Boot Camp, supporting the training of over 30 teachers in fundamental machine learning concepts. Developed interactive dashboards using Tableau and Power BI, analyzing survey data to support professional development decisions, improving event effectiveness by 15%. Conducted in-depth analysis of female student enrollment trends in technology programs over 10 years, using Power BI and Tableau to deliver insights and recommendations that contributed to a 25% increase in female participation in STEM initiatives. Created STEM lesson plans on data storytelling, utilizing Tableau, Matplotlib, Seaborn, and ggplot2 in Python, engaging over 200 students in hands-on data analysis activities. Produced an educational video demonstrating Power BI visualization and trend analysis using gaming sales data, with 75% positive feedback from participating students. Designed and led STEM activities using Excel to teach students data-driven decision-making using Data Analytics. Generated data reports and pivot tables from GenCyber Teacher Camp survey data, streamlining feedback analysis for over 50 teachers.Analytics Assistant Manager 11/2020 to 10/2022Karur Vysya Bank Chennai, India Led data analytics and reporting initiatives across multiple departments, delivering tailored solutions that enhanced business intelligence and decision-making processes, resulting in a 20% improvement in operational efficiency. Utilized SQL to pull data from FRS (Financial Reporting System), analyzing customer spending behavior for targeted sales of credit cards, home loans, and car loans. Successfully optimized product offers based on spending patterns, leading to a 15% increase in credit card sales. Conducted risk analysis for fraud management by generating security rules based on customer spending history, reducing fraud incidents by 10%. Collaborated with management departments to understand data needs, creating dynamic reports and dashboards in Power BI, delivering actionable insights to key stakeholders and improving decision-making processes by 25%. Analyzed and interpreted complex data sets, identifying trends, risks, and opportunities, leading to recommendations that improved business outcomes by 18%. Continuously improved analytics processes by staying updated on industry best practices and emerging technologies, enhancing data analysis tools, which reduced reporting time by 30%. Assistant Systems Engineer 10/2017 to 07/2019Tata Consultancy Services Hyderabad, Telangana Collaborated with Daimler to analyze business requirements and develop comprehensive test cases, enhancing test coverage and minimizing defects. Utilized CIAT tools for generation, verification, and execution of test cases for software modules in automotive functional testing, collaborating closely with the client as a Test Engineer. Analyzed and reported simulation and test data results for Advanced Driver Assistance Systems (ADAS), ensuring accuracy and compliance with automotive safety standards. Conducted root cause analysis for system failures during functional testing, providing actionable insights to improve system reliability by 10%.EducationMaster of Science: Business Analytics 09/2022 - 07/2024 Grand Canyon University - Phoenix, AZ Relevant Coursework: Introduction to Databases & Descriptive and Diagnostic Analytics & Predictive Analytics 3.93 GPA. Ranked in Top 4% of class Research Project: Detection of Loan Defaults Predicted customer loan default probability using Logistic Regression on the Loans Dataset, selecting the top features and identifying 15% of fraudulent cases, leveraging Pandas, NumPy, and SQLAlchemy for data analysis. Generated over 20 aggregated analytical summaries on customer loan default behavior, documenting insights for further business analysis and strategic decision-making.Post Graduation Diploma: Banking Technology 06/2019 - 07/2020 IDRBT - Hyderabad, India 3.6 GPABachelor's of Technology: Electronics And Communication Engineering 07/2013 - 05/2017 Vellore Institute of Technology - Vellore, India 3.5 GPA |
