Power Bi Data Analyst

Satya Pradeep Kodeboina

Columbus, OH (Open to relocate) +1-857-***-**** ****************@*****.*** Power BI

SUMMARY

Data Product Owner and Business Intelligence Developer with 7 years of experience delivering data-driven solutions in Agile environments. Proven expertise in SQL, SAS, Python, Power BI and AWS, with a strong background in stakeholder collaboration, data product lifecycle management, and documentation. Available for immediate onboarding and ready to relocate.

SKILLS & CERTIFICATIONS

Data Analysis: MySQL, SQL, Python (Pandas, NumPy, Matplotlib, Sklearn), R (dplyr, ggplot2, tidyr), SAS, Advance Excel (Pivot, VBA, Macros)

Business Intelligence: Power BI, SAS, Tableau, AWS, QuickSight, Snowflake, Jira, Salesforce Analytics, Google Analytics (Tera Desk)

Data Mining: Informatica, Collibra, ETL scripting, Exploratory Data Analysis (EDA), Data Preprocessing, Data Modeling, AWS (S3, EC2, Redshift)

Machine Learning: Predictive Analysis, Random Forest, Logistic Regression, K-NN, SVM, Monte Carlo Simulation, Decision Trees

Certifications: Microsoft Power BI (PL-300), Tableau Data Analyst Desktop Certification, Amazon Web Services (AWS) for Data Analytics.

WORK EXPERIENCE

Data Analyst Nationwide Insurance Columbus, OH Jul 2023 – Aug 2025

Cleaned and transformed complex datasets using SQL, SAS, and Python to ensure data integrity and consistency across fraud prevention programs. Applied data validation and formatting protocols to produce reliable outputs for statistical analysis and reporting.

Designed and implemented end-to-end data preprocessing pipelines in Snowflake, SAS and Python, addressing missing values, outliers, and schema mismatches, supporting fraud detection models and mirrored best practices for healthcare data cleaning, improving data readiness.

Created customized data briefs, visual dashboards, and formatted tables using Power BI and SAS tailored for business executives, compliance teams, and fraud strategists. Outputs emphasized actionable insight and facilitated evidence-based decision-making in audit environments.

Conducted internal literature reviews and secondary research on fraud analytics best practices within insurance and healthcare domains, summarizing findings into stakeholder presentations and internal documents that aligned modeling strategies with industry standards.

Participated in weekly peer learning sessions with cross-functional data analysts and early-career professionals.

Contributed case studies, facilitated knowledge exchange on data communication practices, and continuously improved approaches to stakeholder engagement, aligning analytics outputs with real-world decision-making needs.

Senior Data Analyst – North America Last Mile Logistics Amazon India Dec 2019 – Jul 2021

Developed automated QA/QC pipelines for both inventory and transportation datasets using Python (Pandas) and R (dplyr), integrating Esri ArcGIS, Informatica, and Collibra governance rules to improve data accuracy by 18% and reduce supply chain disruptions.

Queried inventory and spatial data using SQL window functions and built Excel (VBA) models to identify inefficiencies in material flow and route planning; visualized KPIs such as stock availability, fuel efficiency, and delivery accuracy in Power BI, leading to $80K in annual cost savings.

Built interactive Power BI dashboards using DAX and custom visuals to track SLA compliance, inventory turnover, backlog trends, and route-level performance; enabled leadership to proactively address delivery risks and material shortages.

Partnered with Data Engineering to define metadata standards and data lineage across inventory and GIS sources using Collibra, improving traceability and compliance across the transition process.

Conducted root cause analysis of delayed replenishments and outlier delivery routes using clustering and spatial joins in Python and ArcGIS, supporting strategic planning for inventory positioning and transition timing.

Data Analyst – North America Transportation Ops Support Amazon India Nov 2017 – Nov 2019

Consolidated and cleaned customer operations data using SQL and Python (Pandas, NumPy); performed exploratory data analysis (EDA) to improve data completeness and accuracy by 15%, integrating validation rules via Informatica and Collibra.

Developed and deployed “Fixit!” logic in Hubble and ETL tools to monitor scan hygiene in zone picking & packing; reduced scan errors by 20% and saved over 200 man-hours weekly across multiple fulfillment centers.

Created interactive dashboards to visualize KPIs such as delivery efficiency, customer satisfaction, and process adherence using Jira, Excel, and Salesforce Analytics; led to a 10% improvement in stakeholder satisfaction and 18% faster project delivery.

Administered the Social Media Escalations project, analyzing over 400 customer issues related to Returns, Delivery, and Quality using Salesforce Analytics and AWS QuickSight; reduced average response time by 15% and improved customer retention.

Partnered with cross-functional teams to define data requirements, develop user stories, and prioritize backlog tasks; translated business needs into technical solutions to support regional ops teams.

Data Analyst – Logistics Campaigns Orange Leaf India Jul 2016 – Oct 2017

Collaborated with marketing teams to analyze email and social media campaign performance, using SQL and SAS to identify conversion patterns and optimize segmentation strategies, contributing to a 15% boost in engagement and lead generation.

Partnered with marketing and donor engagement teams to analyze campaign performance using SQL and Google Analytics; segmented donor lists based on engagement behavior and optimized targeting strategies, leading to a 20% increase in email open and click-through rates.

Visualized KPIs including web traffic, unique visitors, and email click-through rate using Google Analytics, optimizing digital marketing strategies using SEO and email marketing increasing online donations by INR 20,000 monthly

Utilized social media analytics tools Hootsuite and Buffer to monitor and report campaign performance, comparing insights like skip rate and completion rate, using strategic marketing to understand suitable length of ads improving engagement rates by 26%.

EDUCATION

Master of Science, Data Analytics Sep 2021 - May 2023

Northeastern University, Boston, MA, GPA: 3.8/4

Courses: Probability and Statistics, Predictive Analytics, Database Management systems, Data Mining applications, Machine Learning, Visualizations

Bachelor of Technology, Computer Science Jul 2012 - May 2016

Vignan University, Guntur, India, GPA: 3.5/4

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