Data Analyst Machine Learning

Krishithanjali Vemuri

USA +1-513-***-**** ********************@*****.*** https://www.linkedin.com/in/krishithanjali/ SUMMARY

Data Analyst with 3 years of experience and a strong foundation in Data Engineering. Proficient in SQL, Python, and BI tools such as Power BI and Tableau. Experienced in data wrangling, analysis, building efficient ETL pipelines, and developing machine learning models for predictive and prescriptive analytics. Adept at transforming complex datasets into actionable insights to support data-driven decision-making and optimize business processes. SKILLS

Data Analysis & Visualization: Power BI, Tableau, Excel, Dashboard Storytelling Programming & Querying: Python, SQL

Machine Learning & AI: Predictive Modeling, Classification, Regression, Clustering, Feature Engineering, Model Evaluation

(Precision, Recall, ROC-AUC), Scikit-learn, XGBoost, Pandas, NumPy Data Engineering: ETL Development, Data Pipelines, Data Modeling, Data Integration Database Technologies: MySQL, PostgreSQL, MS SQL Server Cloud Platforms: Azure, AWS

Data Handling: Data Cleaning, Transformation, Wrangling, Validation Tools & Technologies: Jupyter Notebook, Git, VS Code, Azure DevOps Soft Skills: Critical Thinking, Communication, Stakeholder Collaboration, Problem Solving PROFESSIONAL EXPERIENCE

Data Analyst, Target Corporation Jun 2024 - Present USA

Developed and maintained Power BI and Tableau dashboards, providing real-time insights on business metrics like customer behavior and sales trends, reducing reporting time by 13% and helping teams make faster, more data-driven decisions through dashboard storytelling.

Partnered closely with business teams to refine key data metrics and align reporting tools with overall business objectives such as KPIs and OKRs, improving the consistency and accuracy of critical business reports.

Extracted, cleaned, and analyzed large datasets using SQL and Python, identifying actionable trends and delivering insights that directly influenced marketing and operational strategies, including churn prediction models that enhanced customer retention by 10%.

Collaborated with the data engineering team to automate data pipelines using Azure Data Factory, streamlining workflows and accelerating reporting timelines by 24%, while also enhancing overall data integrity and consistency.

Built and deployed machine learning models using Python and scikit-learn to forecast sales demand and optimize inventory allocation, improving stock availability and reducing overstock incidents. Data Engineer, Amazon Sep 2022 - Jul 2023 India

Utilized AWS Glue to transform raw, unstructured data into a clean, structured format ready for analysis, decreasing manual data processing time by 13% and ensuring higher-quality data for decision-making.

Designed and maintained ETL pipelines to automate the transfer of data into AWS S3, significantly reducing the time spent on manual data entry and improving overall processing efficiency, allowing teams to access data more quickly and reliably.

Managed AWS cloud storage, optimizing data access and reducing associated storage costs by 11%, while ensuring scalability and robust performance of data storage for future use.

Developed and implemented automated data quality checks, reducing data entry errors by 12% and significantly improving the reliability of downstream analytics.

Worked with cross-functional teams to align data needs and deliver presentations guiding reporting and infrastructure decisions. Data Analyst, Wipro Sep 2021 - Aug 2022 India

Performed detailed data entry tasks and data cleaning using SQL and Python, ensuring consistency and accuracy in datasets, which reduced reporting discrepancies and enhanced data trustworthiness for key business decisions.

Created and maintained Power BI dashboards to track essential business KPIs, allowing stakeholders to easily access and interpret data, reducing reporting time and making business insights more accessible to teams.

Automated key data workflows using Azure Data Factory, reducing repetitive data tasks by 24% and accelerating data processing, which increased team productivity and reduced reporting delays.

Cleaned and structured large datasets to ensure they were accurate and consistent, reducing errors in business reports and improving reporting accuracy and data quality across the organization.

Supported A/B testing scenarios by preparing segmented datasets to assess performance impacts across marketing strategies. PROJECTS

Real-Time Stock Market Data Pipeline

Engineered a real-time machine learning pipeline leveraging Apache Kafka and Spark Streaming to seamlessly capture, process, and analyze continuous streams of stock market data, enabling sub-second insights for high-frequency decision-making.

Implemented advanced predictive models, including LSTM networks, Prophet forecasters, and XGBoost, enriched with dynamically computed technical indicators (MACD, RSI, Bollinger Bands) to enhance forecast precision for price movements and volatility shifts.

Automated the end-to-end model lifecycle in AWS SageMaker, incorporating drift detection mechanisms and conditional retraining workflows to sustain accuracy under rapidly changing market dynamics.

Delivered actionable intelligence through a real-time alerting framework powered by AWS Lambda and a Power BI analytics dashboard, empowering stakeholders to monitor live trends, assess risk, and act on critical market events. Real-Time Ride Demand Forecasting & Dynamic Pricing

Designed a real-time forecasting system using Apache Kafka and Spark Streaming to process historical and simulated ride-hailing data, enabling near-instant analysis of demand fluctuations across geographic zones.

Implemented time series models (LSTM, Prophet) alongside a Reinforcement Learning agent (PPO algorithm) to optimize dynamic pricing strategies, resulting in an 18% improvement in simulated profit margins.

Automated deployment and retraining workflows in AWS SageMaker, integrating model drift detection to maintain predictive reliability under shifting market conditions.

Delivered real-time operational insights through a Power BI dashboard and AWS Lambda alerting system, empowering decision- makers to monitor demand trends, surge pricing triggers, and model performance in production. EDUCATION

Master of Science in Information Technology

University of Cincinnati, Cincinnati, OH Aug 2023 - Dec 2024 Bachelors of Technology in Computer Science Engineering DVR & Dr. HS MIC College of Technology, Kanchikacheria, India Aug 2019 - May 2023 CERTIFICATIONS

AWS Certified Solutions Architect

SQL Proficiency – Verified through LeetCode SQL Badge

AWS Certified Machine Learning – Specialty AWS, ML pipeline design, deployment

Databricks Certified Machine Learning Professional

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