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                                                                   Candidate's Name
                                PHONE NUMBER AVAILABLE EMAIL AVAILABLE   LINKEDIN LINK AVAILABLE
                                           Eligible for full-time opportunities starting (Aug Street Address )

EDUCATION
University of Cincinnati, Carl H. Lindner College of Business                                                                                      Cincinnati, Ohio
Master of Science, Business Analytics                                                                                                                    Aug Street Address
(Intelligent Data Analysis, Stats Method, Time series Forecasting, Data Mining, Data Visualization, Logistic Regression, Optimization, Finance Foundation)
Sagi Rama Krishnam Raju Engineering College, Andhra Pradesh, India                                                                              Bhimavaram, India
Bachelor of Technology, Electronics and Communication                                                                                                  Sep 2020

SKILLS
Cloud: AWS (S3, Redshift), Google(Big Query, Google Cloud Storage ,Data Proc, Data Flow)
Databases: MYSQL, SQL Server, NoSQL, MongoDB,
Tools: Tableau, Power BI, Alteryx, Advanced Excel, Sccm and Imaging,HR Analytics, Snowflake, QuickSight
Programming: Python (NumPy, Pandas, scikit-learn), SQL, NLP(Lower level),Big-Data(Hadoop,Spark,HIVE,PIG)
Statistics & Algorithms: Regression, Classification, Resampling Methods, Decision Tree, Random Forest, Clustering, LDA,
                 Variable Selection, Central Limit Theorem, Point Estimates, confidence & prediction intervals, A/B Testing
Mathematics: Probability, Linear Algebra, Vector Algebra, Calculus
WORK EXPERIENCE
Research Graduate Assistant, University of Cincinnati(P& G Comapny )                                 Jan 2024 - May 2024
     Developed an NLP pipeline using NLTK and Python to preprocess and analyze ServiceNow ticket data,
       implementing Flan T5 XXL for text summarization and optimizing performance with BERT and Hugging Face
       models. Applied LDA clustering to identify recurring issues, visualizing results with pyLDAvis. This solution
       reduced ticket resolution times by 35%, saving the company approximately $50,000 annually and improving
       overall operational efficiency.
 Data Analyst, Infosys, Jonson Controls Client                                                    June 2022   June 2023
      Performed Feature Engineering on large datasets using regression and statistical methodologies, including
       Random Forest; built models that improved forecasting accuracy by 25%, significantly enhancing strategic
       planning and decision-making processes.
           Collaborated with technical team to create Splunk dashboards to provide a holistic view of Project schedules,
           Status reports, Issue logs as part of an optimization process leading to reduction of 30% in the number of incidents
           breaching deadlines.
           Utilized Agile methodologies to streamline project workflows, reducing development cycle time by 30% and
           increasing team productivity by 25%.
        Implemented and optimized ETL processes for SCCM data using Snowflake, resulting in enhanced data ingestion
        and loading efficiency. By leveraging Snowflake s capabilities, improvements to the ETL workflows increased
        data integrity by 35% and accuracy by 40%, leading to a substantial boost in overall operational efficiency.
  Associate, Infosys,Max life Insurance                                                                   Feb 2021   May2022
      Utilized SQL to analyze policyholder and claims data, enhancing decision-making and understanding of insurance
        coverage requirements. Developed complex stored procedures that improved data retrieval speed by 35% and
        increased the accuracy of claims reporting by 25%.
           Designed and developed interactive dashboards in Power BI using DAX calculations to support underwriting and
           claims analysis. Implemented complex calculated columns, resulting in a 30% improvement in the accuracy of
           premium and claims projections.
           Led recurring and ad-hoc data analysis projects, aligning with business objectives to support strategic decision-
           making. This initiative resulted in a 30% reduction in project turnaround time for risk assessment and claims
           processing.
           Created dynamic visual reports in MS Excel using VBA, pivot tables, Power Query, and VLOOKUP. These
           reports tracked policy renewals, claims settlements, and customer data, improving data retrieval speed by 40%
           and decision-making accuracy by 30%.
           Conducted EDA on insurance data to extract insights into claims patterns and policy risks. Communicated key
           findings to underwriters and business stakeholders, ensuring data integrity across policy management and claims
           processing for a diverse insurance portfolio.