Akhil Golla Email & Phone Number

Atlanta, Ga, Us

Atlanta, Georgia, United States

• Developed and maintained Python scripts using the Beautiful Soup library for automating data collection by web scraping multiple illicit Telegram channels, improving efficiency and saving 75% of time compared to manual processes by enabling automated and reusable scraping workflows.• Analyzed unstructured chat data from multiple channels and created impactful visualizations in Tableau, enabling stakeholders to make informed decisions 50% faster and improving operational efficiency.• Created an automated chatbot using Python, Selenium, and Wit AI to generate automatic responses across 20 teen chat rooms, enabling data collection for an online honeypot awareness project, which contributed to safeguarding millions of teens from potential online threats.• Leveraged NLP techniques such as TF-IDF and sentiment analysis to extract key insights, popular content, and contextual patterns from Telegram channels, enhancing channel dynamics understanding and enabling actionable insights. This analysis improved decision-making efficiency by 40% for stakeholders addressing critical channel activities.• Designed and implemented an automated Python solution utilizing OCR (Optical Character Recognition) to detect and eliminate image duplication, achieving a 50% improvement in analysis efficiency. Integrated the solution with the Dropbox API to streamline data management and ensure seamless processing.

Atlanta, Georgia, United States

• Developed, scaled, and deployed a time series forecasting model using SARIMA to predict future case volumes from each facility and state. This enabled the company to proactively plan resources and optimize physician scheduling, leading to an 80% increase in operational efficiency by accurately forecasting volumes in advance.• Built an LSTM neural network ML model to forecast physician scheduling based on predicted case volumes, optimizing resource allocation, reducing scheduling conflicts, and saving $1 million annually by preventing overpayments to underutilized physicians.• Worked on developing a clinical note summarization system leveraging the BioBART large language model (LLM) to process over 1 million cases, significantly reducing the time required for physicians to revisit and review cases, improving workflow efficiency and enhancing patient care outcomes.• Created dynamic Tableau dashboards to visualize key metrics across departments including Physician Credentialing, Marketing, Medical Staff Division, Onboarding, IT, and HR. These dashboards delivered actionable insights, enhancing decision-making processes by 40% and improving operational outcomes.• Established and managed connections between Tableau, Salesforce, Five9, and SQL Server, streamlining data flow and enabling real-time access to processed data. This reduced reporting delays by 50%, enhancing analysis speed and efficiency.• Utilized Azure Data Studio to write SQL queries, extracting and preparing datasets for dashboards and reports. This improved data accuracy and reporting timelines by 30% across multiple departments.• Designed and maintained ETL pipelines to integrate patient case data with key metrics seamlessly, enabling accurate analysis and reporting. This streamlined hospital decision-making processes and reduced manual data processing efforts by 45%.

Atlanta, Georgia, United States

• Developed a claim price prediction model using Random Forest and Decision Tree algorithms withensemble stacking, achieving an R² score of 0.92. This enhanced accuracy helped identify and mitigate claim discrepancies, reducing financial losses by 50% and saving millions annually.• Maintained and managed machine learning models deployed in Docker environments, resolvingenvironment-related issues and ensuring consistent model performance and reliability across production systems.• Improved model transparency by implementing SHAP and LIME for interpretability, enabling seamless communication of insights to non-technical stakeholders and fostering informed decision-making.• Optimized data processing efficiency by 40% through advanced SQL queries in Snowflake, enabling faster data management workflows and enhancing training processes for machine learning models.• Created interactive Tableau dashboards to track and analyze claim trends, visualize key performance metrics, and uncover patterns in claim overpayments. These dashboards empowered leadership to make data-driven decisions and adopt more strategic claims management practices.

Hyderabad, Telangana, India

• Conducted thorough data quality analysis through Exploratory Data Analysis (EDA) utilizing SQL, Python, and Pandas, ensuring data accuracy and reliability.• Developed machine learning regression models to predict day-to-day transactions and track customer behavior across multiple locations, as well as sales and returns in various categories, resulting in a remarkable 25% month-over-month increase in sales.

Hyderabad, Telangana, India

• Developed interactive Tableau charts, dashboards, and stories by aggregating customer sales and revenue data at various time levels, providing valuable insights for business decisions.• Utilized SQL scripting to ensure data integrity and validate updated information across different modules, ensuring accuracy and reliability.• Conducted statistical analysis to perform root cause analysis of problems, leading to the identification of action areas and an impressive 15% improvement in productivity.• Introduced automation ideas and automated scripts, significantly reducing manual work by approximately 70% and saving around 60 hours per month.

Hyderabad, Telangana, India

As a Data Analytics Intern at SplashBI, I contributed to automating daily job activities and improving data management processes. My key activities included:1) Process Automation: Saved 75% of human effort and time by automating a daily job activity using shell/bash scripting, resulting in significant operational efficiency.2) Data Quality Monitoring: Assisted in preprocessing data and ensured data quality and consistency using MySQL, improving the reliability and accuracy of business processes.Key Learnings:-> Developed strong skills in automation through shell/bash scripting, leading to enhanced efficiency in recurring tasks.-> Improved my understanding of data quality management and preprocessing techniques using MySQL, ensuring data reliability and accuracy.-> Acquired valuable experience in a dynamic startup environment, streamlining workflows and showcasing the tangible benefits of automation in day-to-day business operations.

Master Of Science - Ms, Computer And Information Sciences (Big Data Analytics), 3.93

Courses: 1) Big Data Infrastructure 2) Data Programming (Python & RStudio) 3) Unstructured Data Management 4) Information Security 5).

Bachelor Of Technology, Electrical, Electronics And Communications Engineering, 3.5

Activities and Societies: -> Took an initiative to display working model of major project in college level science fair. -> Participated.