Data Analyst Machine Learning

PALIVELA TARUN

Data Analyst

Location: CA, USA Email : ***************@*****.*** Phone: 341-***-**** LinkedIn Summary

* ***** ** ********** ** a Data Analyst specializing in predictive analytics, machine learning, and data visualization to drive business and operational improvements.

Proficient in Python, SQL, and cloud platforms (AWS, Google Cloud, Microsoft Azure) for data-driven decision-making and pipeline optimization.

Expert in ETL workflows and data profiling, including generating Gap Analysis reports and ensuring data consistency across systems.

Skilled in designing semantic models for Power BI and providing solutions for EDP/Data Marts, enhancing reporting efficiency.

Proven ability in creating STTM and BRD documents, and analyzing normalized/denormalized models, Fact and Dimension tables, and Type 2 Slowly Changing Dimensions.

Experience with data storage and processing solutions like AWS S3, Google Big Query, and Google Cloud Storage, ensuring scalability and security.

Proficient in machine learning techniques, including Linear Regression, Random Forest, Decision Trees, and KNN, to solve complex business challenges.

Adept at building interactive dashboards with Tableau and Power BI to visualize KPIs and enable actionable decision-making.

Strong expertise in healthcare analytics tools (HIPAA, EMR, EHR), ensuring secure and compliant data analysis in healthcare environments.

Skilled in data wrangling, cleaning, and transformation, preparing large datasets for analysis and delivering actionable insights. Skills

Programming: Python, C, SQL

Libraries: NumPy, Pandas, SciPy, Seaborn, Matplotlib, Scikit-Learn, Beautiful Soup, NLP Databases: MySQL, MS SQL, MongoDB, Oracle

Visualization Tools: Power BI, Advanced Excel, Tableau Methodologies: SDLC, Agile, Waterfall

Data Integration Tools: Informatica

Cloud Technologies: AWS (EC2, EBS, S3, Lambda), Microsoft Azure, Google Cloud (Big Query, Dataflow, Pub/Sub, Cloud storage) Big Data Systems: HDFS, MapReduce, Hive, HBase, Airflow Machine Learning Techniques: Regression, KNN, Decision Tree, Naive Bayes, Random Forest Tools: Git, Visual Studio Code

Healthcare Tools & Technologies: HIPAA, EMR

Analytical Skills: Data Cleaning, Data Mining, Data Warehousing, Statistical Modelling, Data Wrangling, ETL, Data Visualization, SAP Professional Experience

CVS Health August 2024 – Present

Data Analyst

Developed predictive models using Python and SQL to forecast healthcare service utilization (e.g., pharmacy visits, and clinic appointments) based on historical data.

Applied machine learning algorithms (e.g., Linear Regression, Random Forest) to identify key factors affecting healthcare demand and optimize resource allocation.

Designed interactive Tableau dashboards for real-time monitoring of service utilization trends, enabling data-driven decision-making across healthcare teams.

Collaborated with cross-functional teams to refine models and ensure alignment with operational goals, enhancing forecast accuracy and efficiency.

Provided actionable insights to senior management, improving patient care planning, reducing wait times, and optimizing healthcare service delivery.

Tatva Soft August 2021 – July 2022

Data Analyst

Analysed supply chain operations to uncover cost-saving opportunities and improve delivery timelines for a major manufacturing client.

Extracted and processed extensive datasets using SQL and Python (Pandas), ensuring high accuracy and consistency for comprehensive analysis, with cloud data storage on Google Cloud Storage.

Built linear regression models to pinpoint key factors affecting lead times, enabling proactive mitigation of delays using Google Cloud AI tools.

Created interactive Tableau dashboards to monitor delivery performance metrics, including on-time rates, supplier efficiency, and transportation expenses, leveraging over 100,000 data points, integrated with Google Big Query for real-time data querying.

Streamlined data consolidation through wrangling and transformation techniques, enhancing quality and efficiency across diverse sources, using Google Cloud Dataflow for ETL processing.

Automated weekly reporting using Python scripts, minimizing manual effort and improving reporting speed and reliability, leveraging Google Cloud Functions for automation.

Delivered actionable recommendations to senior management, supporting strategic decisions that strengthened supplier relationships and optimized operational performance.

Partnered with supply chain and operations teams to devise strategies that elevated supplier efficiency and cut transportation expenses. Trigent June 2020 – July 2021

Data Analyst

Collaborated with cross-functional teams to collect, clean, and process large datasets using Python, SQL, and AWS tools, ensuring accuracy for predictive modeling and cloud-based data integration.

Analysed business operations to evaluate the impact of COVID-19 on sales, supply chain, and customer behavior across various regions, utilizing AWS S3 for data storage and EC2 for processing.

Developed time series forecasting models to project the pandemic’s ongoing effects on business performance, utilizing both historical data and real-time metrics via cloud infrastructure.

Designed interactive Power BI dashboards and utilized AWS CloudWatch to monitor key performance indicators (KPIs), including sales declines, recovery rates, and customer engagement trends.

Delivered actionable insights to leadership, enabling better decision-making for business continuity planning and resource allocation, leveraging AWS Lambda for automation and real-time data processing.

Created automated ETL workflows using Python, SQL, and AWS Glue, enhancing pipeline efficiency and reducing manual intervention across cloud environments.

Applied Advanced Excel for in-depth analysis, including trend identification and customized reporting, supporting strategic decisions.

Conducted validation and transformation to prepare high-quality records for advanced analytics, ensuring consistency and reliability across diverse cloud sources.

Academic Project

Electric Corporation (Decision Tools)

Developed a Linear Programming (LP) model to optimize camcorder manufacturing and distribution, achieving a 10% cost reduction.

Applied statistical analysis and collaborated with cross-functional teams to evaluate key metrics like order size, lead times, and distributor locations, enhancing supply chain workflows. Recognizing Potential Disruption Management Strategies in Supply Chain during COVID-19 Pandemic

Conducted an in-depth analysis of supply chain disruptions, applying statistical techniques to assess and visualize business impact.

Recommended mitigation strategies that improved resilience and decision-making processes through data insights. Evaluating Automation Alternatives for ZUSH Company

Utilized Monte Carlo Simulation to model financial outcomes and assess risks for automation alternatives.

Collaborated with stakeholders to derive data-driven decisions, leading to optimized automation workflows and improved risk management.

Education

California State University, Northridge, California August 2022 – May 2024 Master of Science in Engineering Management

Chaitanya Bharathi Institute of Technology, Hyderabad, India July 2018 – May 2022 Bachelor of Engineering in Electronics and Communication Engineering Certifications

GCP Cloud data Engineer Certificate (2024)

Artificial Intelligence, Verzeo (2020)

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