Dheeraj Kumar Muddasani

Experience

• 

  Datadot Software Solution

  Jul 2017 - Aug 2021

  • Spearheaded a data analytics solution to reduce procurement lead times by analyzing large-scale datasets, using Python, Pandas, and MS Excel, achieving a 15% improvement in process efficiency.• Designed and managed intricate SQL queries, stored procedures, & functions for data retrieval, manipulation across SQL Server environments.• Stored processed data in AWS S3, improving data access speed by 25% and seamless integration for analysis across cross-functional teams.• Transformed financial data into actionable insights using data visualization tools like Power BI and Tableau, enhancing key decisions by 20%.• Utilized Tableau’s dynamic parameters and dashboards to enable real-time, self-service reporting, reducing ad-hoc report requests by 40%.• Leveraged machine learning algorithms to develop predictive models, resulting in a 20% improvement in sales forecasting accuracy.• Coordinated 200+ project tasks in Jira, improving tracking efficiency by 30% and ensuring alignment across cross-functional teams.• Managed CI/CD pipeline using Git for version control & Jenkins for automation, improving deployment efficiency & reducing lead time by 30%.• Architected and implemented 5 AWS projects, optimizing infrastructure, and achieving 35% reduction in operational costs by leveraging services such as AWS Lambda, EC2 auto-scaling, S3, Amazon RDS, API Gateway, Fargate, and SNS/SQS.• Collaborated with cross-functional teams to integrate Python-based automation scripts and deploy REST services.• Led end-to-end development and implementation of ETL processes for data ingestion into a Data Lake, resulting in processed data quality. Show less • Incorporated advanced statistical techniques and data analysis tools, including Pandas, NumPy, Scikit-Learn, and Tableau, to identify key customer segments and preferences, driving a 25% increase in customer satisfaction scores.• Experienced in SQL and NoSQL databases, data validation, cleansing, and visualization tools, resulting in a 99.5% data accuracy rate.• Implemented indexing strategies and query optimization techniques, improving a 30% in database query efficiency. • Created interactive reports and dashboards for a complex projects with 12 teams, integrating real-time key performance indicators (KPIs).• Implemented data structures like arrays, linked lists, and trees to manage large datasets, improving 25% data retrieval & manipulation speed.• Launched a streamlined CI/CD pipeline with Azure DevOps, reducing deployment time and increasing software release frequency by 75%.• Followed best development practices, including rigorous code reviews, comprehensive unit testing, and high demand testing methodologies. Show less

  • Senior Data Analyst

    Feb 2020 - Aug 2021

  • Data Analyst

    Jul 2017 - Jan 2020
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  Neuro-Insight

  Jan 2023 - May 2023

  Business Data Analyst

  While at Neuro Insight, I worked on diverse and cutting-edge data analytics projects, specializing in the assessment of advertising content.Conducted Sentiment Analysis and Speaker Detection:• Utilized Natural Language Processing (NLP) techniques to analyze the sentiment and emotional impact of advertising content, including determining if it was neutral, positive, or negative.• Identified gender-based voices, celebrity speakers, and the number of narrators, offering valuable insights into audience reactions.• Employed advanced speech-to-text recognition algorithms to transcribe and analyze spoken content within the ads.Music Recognition and Visual Analysis:• Employed music recognition algorithms to study the genre and timing of music used in advertisements.• Conducted visual analysis of ads to examine elements such as frozen moments, screen freezes, and animation styles.• Leveraged Assembly AI and Cloud Video Intelligence API to gain a comprehensive understanding of the visual dynamics within the videos, with a particular emphasis on vibrant scenes and lighting.Entity Detection and Object Identification:• Implemented entity detection techniques to identify objects and elements within advertising content.• Calculated average shot and entity confidence levels using machine learning frameworks like PyTorch and TensorFlow.Tableau Dashboard Creation:• Designed and developed Tableau dashboards to visualize and communicate insights from the data.• The dashboards provided actionable insights to stakeholders, resulting in a significant 15% boost in campaign effectiveness and more informed decision-making in the advertising domain.My experience at Neuro Insight allowed me to apply my data analytics skills to real-world challenges in the advertising industry. I gained hands-on experience in advanced data analysis techniques, machine learning, and data visualization, contributing to the success of advertising campaigns and decision-making processes. Show less

• 

  L&T Technology Services

  Oct 2023 - now

  Senior Engineer

  Working for the client, Oncor Electric Delivery.

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  Oncor Electric Delivery

  Oct 2023 - now

  Data Analyst

  • Developed a predictive tool using Python, Spark, and SQL for calculating transformer top oil and hotspot temperatures under varying temperatures and load conditions to improve operational insights and optimize maintenance planning.• Executed over 50 advanced SQL queries in Oracle SQL Developer, ensuring extraction, transformation, loading processes for data analysis.• Compiled and organized data from 10+ diverse sources into Excel, integrating the data into Oracle database for streamlined data management.• Built machine learning algorithms using Python to predict transformer oil and hotspot temperatures, improving prediction accuracy by 20%.• Transformed and normalized data using PySpark, improving data consistency and accuracy across 500,000+ records for predictive modeling.• Leveraged Python for data analysis, handling customer electricity usage, power generation & transformer details, increasing 15% data insights.• Stored processed data in Snowflake within a multi-layer architecture, enabling structured storage for efficient retrieval and analysis.• Automated data pipelines using Python, reducing manual handling by 30% and enabling faster processing of transformer performance metrics.• Conducted thorough exploratory data analysis and implemented sophisticated feature engineering techniques, facilitating root cause analysis.• Developed interactive Tableau dashboards with user-driven filters and drill-down capabilities, allowing stakeholders to explore data trends.• Integrated advanced forecasting features into Tableau dashboards, providing predictive insights and enabling transformer maintenance planning.• Presented findings and collected feedback from stakeholders, enhancing maintenance strategies and improving tool accuracy by 15%.• Utilized Python to develop models that generated maximum temperature values of transformers across various time intervals throughout the month and year, streamlining data analysis process. Show less