Data Analyst

AKASH KUMAR

+1-602-***-**** ********@***.*** LinkedIn GitHub

Results-driven master’s graduate with 4 years of experience, actively seeking full-time opportunities (May’25) as a Data/Business Analyst EDUCATION

Arizona State University- W. P. Carey School of Business Aug 24 – May 25 Master of Science in Business Analytics GPA:4.0/4.0

• Coursework: Enterprise Data Analytics, Machine Learning in Business, Descriptive and Predictive Analysis, Analytics Unstructured Data, Advanced Marketing Analytics, Analytical Decision Modeling

• Leadership and Activities: Member of Sun Devil Data Science and The AI Society, Summa Cum Laude, Dean’s Merit List SRM Institute of Science and Technology, India Jun 15 – May 19 Bachelor of Technology in Electronics and Communication Engineering SKILLS AND CERTIFICATIONS

Programming: Python, SQL, Pandas, NumPy, Matplotlib, Machine Learning, Regression, NLP, Scikit-Learn

Data Management: Data Warehousing, Data Visualization, Data Modeling, MySQL, AWS, Alteryx, SPSS, A/B Testing

Platforms and Tools: Tableau, Microsoft Excel, Excel VBA, PowerPoint, Power BI, Javelin, GIT, Google Analytics, Data Studio

Certifications: Google Data Analytics Certification- Google, Lean Six Sigma Green Belt- AIGPE, Amazon AWS Certified Solutions Architect PROFFESIONAL EXPERIENCE

Decision Analytics Associate Nov 21 – Nov 23

ZS Associates Pune, India

• Project Management: Orchestrated a cross-functional team to implement a reporting solution and technology driven transformation projects for a Fortune 100 pharmaceutical client, managing business operations, benchmarking product performance and driving $800M+ in sales

• Stakeholder Engagement: Designed and implemented data-driven incentive compensation and financial models leveraging linear and logistic regression, created strategic Go-To-Market (GTM) presentations, optimizing sales performance and achieving 12% quarterly sales growth

• Business Intelligence: Built and automated real-time dashboards using SQL, Tableau and Python, developing scripts to automate data extraction, analyzing KPIs and market trends, while delivering actionable business insights and saving 120 hours of manual work

• Data Migration: Spearheaded the migration from SAS to AWS, improved reporting and BI efficiency by 70% by implementing ETL pipelines on AWS (Redshift, S3 and Sagemaker), optimizing SQL for reusable cloud data processing, and ensuring data integrity with robust error handling

• Statistical Analysis: Designed a financial tool to gather requirements and forecast budgets using pricing research and statistical models, enabling clients to track KPIs/metrics, identify root causes of payment variances, and decrease review time from 2 weeks to 1 day

• Quality Assurance and Reporting: Established quality check workbooks using advanced Excel functions and SQL, leading to a 90% reduction in defects and ensuring 100% accurate payouts for sales of over 800+ reps, enhancing data accuracy and risk management System Engineer (Business Intelligence Analyst) Nov 19 – Nov 21 Infosys Chennai, India

• Cross Functional Collaboration: Collaborated with a cross-functional team to analyse service performance, market trends, and financial data using SQL, Excel and Tableau identifying market positioning opportunities and optimizing operations, leading to a 120% revenue increase for a Fortune 100 company

• Data Processing and Optimization: Streamlined the data ingestion process by implementing ETL data pipelines and optimizing SQL queries, which reduced processing time by 32 business hours per week and generated an annual savings of $440K

• Predictive Data Modeling: Partnered with data scientists to design and deploy a demand forecasting machine learning model using XGBoost and Random Forest, improving forecast accuracy by 25%

• Process Automation: Built an automated Python framework for efficient daily data collection, exploratory data analysis, tracking, and rectification of erroneous transactions on a weekly basis, increasing process efficiency by 50%

• Data Visualization and Analysis: Developed and visualized data insights using advanced Excel and Tableau, identifying trends and improving efficiency by 35%

RESEARCH PUBLICATION AND PROJECTS

• Unravelling the Elements of Effective Altruistic Appeals through ML and NLP GitHub Published in Springer's Studies in Computational Intelligence (BICA*AI), developed a machine learning model integrating sparse text vectors and dense features to analyse behavioural data, achieving 75% accuracy in predicting the success of altruistic appeals on Reddit

• Analyzing Sports and Dining Trends GitHub

Analyzed and investigated potential correlations between local sports team performance and customer sentiment in sports-centric restaurants using VADER sentiment analysis, logistic regression, BERT topic modelling and Tableau

• Life Insurance Sales GitHub

Analyzed and predicted agent bonuses to enhance performance and optimize business outcomes for a top life insurer using Python, SQL, Tableau, and ML, improving RMSE by 12%. Identified key drivers like Sum Assured and Customer Tenure.

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