Data Analyst Power Bi

Jayavardhan Reddy Samidi

940-***-**** **********************@*****.*** Linkedin Miami, FL

SUMMARY

• Analytical Data Analyst with 3+ years experience turning raw datasets into actionable insights across finance, sales, marketing, logistics, and healthcare. Skilled in automated reporting, modular workflows, and statistical modeling, with expertise in stakeholder engagement, root cause analysis, and deploying cloud-based, data-driven solutions. EDUCATION

Masters in Data Science and Artificial Intelligence, Florida International University, Miami, Florida 2024 Bachelor of Engineering in Electronics and Communication, Osmania University, Telangana, India 2022 TECHNICAL SKILLS

Algorithms & Data Structure: Arrays, Trees, Graphs, Hash Maps, Sorting (Quicksort, Mergesort). Machine Learning Algorithms and Techniques: Decision trees, Gradient Boosting, LightGBM, LSTM, NLP. Database: MySQL, SSMS, SQL.

DevOps Tools: Git,, Azure.

Big Data Techologies:,PySpark, Spark SQL.

Advanced Data Visualization: Power BI, Tableau, Matplotlib, Seaborn. WORK EXPERIENCE

Business Intelligence Analyst A.P.Moller – Maersk Aug 2024 - Present

• Developed comprehensive Power BI reports integrating fact tables (Shipment History, Transport Plans), with optimized joins and relationships to analyze cancellations and customer transfers, improving issue identification speed by 30%.

• Designed and delivered interactive Power BI dashboards for market managers to analyze volume allocation and revenue trends across trades, customers, and cargo types. Integrated 10+ sources in Azure Databricks using Python, ensuring consistent business logic and marketing insights.

• Built dynamic Power BI dashboards integrating Salesforce CRM with financial data to track pipeline status, EAV, budgets, and goals across North & Latin America, boosting forecast accuracy by 25% and optimizing resource allocation by 20%.

• Designed and maintained SQL Server databases in SSMS, creating and optimizing complex queries, stored procedures, and indexes to support finance, sales, and operations reporting across global business units.

• Performed EDA, data cleaning, and created visual dashboards with Pandas, Matplotlib, Seaborn, Power BI to reveal temporal trends, port traffic, bottlenecks, supporting forecasting, and maintained DAX logic.

• Developed and deployed LightGBM regression models with feature engineering in Python (rolling averages, event markers), achieving 71% accuracy, and operationalized via Azure ML endpoints for BI integration.

• Developed Python-based analytics on dispute case data from CRM and support logs, applying A/B testing to evaluate prioritization and escalation workflows, which improved resolution speed by 35% and enhanced team responsiveness. Data Analyst Edurun Group Jul 2021 – Dec 2022

• Consolidated patient feedback data (surveys, emails, support logs) from Azure Data Factory, SQL, and Databricks, applying text preprocessing to standardize inputs and ensure consistent reporting across teams.

• Conducted sentiment and trend analysis using Pandas, Seaborn, and DAX, calculating sentiment ratios, keyword frequencies, and satisfaction indices, enabling clinical teams to track service quality across 10+ departments and identify areas for targeted interventions.

• Delivered real-time sentiment tagging and reporting using an LSTM model on processed patient feedback, integrating results into dashboards that reduced response time to negative feedback by 20%, improving overall patient experience.

• Consolidated POS transaction data from 50+ retail stores using Power Query and Python into a centralized Azure Synapse environment, enabling consistent reporting and quarterly trend analysis that supported inventory optimization across regions.

• Analyzed refunds, discounts, and stock variances using Python, and SQL, helping finance teams identify profit leakage of ~$250K annually and define actionable KPIs to improve financial controls.

• Conducted fraud risk analysis on transactional data, applying a Random Forest model to flag suspicious activity with 65% precision, and automated reporting for faster decision-making.

Data Analyst Intern Edurun Group Jan 2021 – Jun 2021

• Streamlined dispute and transaction records from multiple systems into a single source of truth, reducing manual reporting time by 30% through automation with Power Automate and improving overall reporting consistency.

• Performed detailed ad-hoc analysis with Excel and SQL to investigate SLA breaches, recurring dispute patterns, and account-level variances, producing actionable reports that supported leadership reviews and strategic interventions.

• Conducted predictive outcome analysis on dispute cases using an XGBoost model, integrating results into interactive dashboards that improved resolution forecasting accuracy by 22%.

PROJECTS

Late Delivery Predicting Model

• Enhanced on-time delivery predictions by using Gradient Boosting and LightGBM on 200,000 customer orders, improved further with effective data processing and clear visualizations in Tableau to aid understanding and decision-making.

• Boosted delivery accuracy by 20% by meticulously crafting targeted feature engineering strategies and deploying sophisticated predictive analytics, showcasing deep expertise in data manipulation and modeling efficiency.

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