Narottam Jajodia

Experience

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  MEHTA EQUITIES LTD

  Apr 2015 - May 2015

  Summer Intern

  • Prepared IPO reports, financial profit & loss models, investment presentations and conducted data analysis using Excel.• Studied several Companies’ Prospectus on SEBI website, and performed other research related to financial markets.

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  Morgan Stanley

  Jun 2017 - Jul 2021

  Business Analyst

  • Analyzed and visualized large data (1M+) and communicated strategic insights to senior management that led to closure of 500+ trade fails monthly, thus reducing operational risk.• Created/updated SQL queries to extract 120+ custom data-views annually, by mapping stakeholder requirements with relational databases, that helped clients prepare critical business reports.• Automated 8 manual Excel reports using VBA macros, solving problems of human error & resource limitation, to save 40 hours of weekly team time, resulting in 15% cost savings.• Developed a Panorama dashboard, in collaboration with cross-functional teams, to generate insight into 20+ critical business indicators for clients and saved total 30 hours of weekly manual effort.• Managed project and led team of 4 to gather & analyze data and influence 500+ stakeholders to review 50,000+ system accesses annually, thereby strengthening information security.• Performed root cause analysis by mining data for 1000+ complex risk incidents (50,000+ data points) and used trends to improve control strategies & build comprehensive reports, thereby increasing efficiency by 33%.• Received firm award (top 4% employees) for initiative that enforced 95% completion of delinquent report submissions by global managers, using research, subject matter expertise, relationship building, effective communication, and training. Explained issues and resolutions to technical and business stakeholders. Show less

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  University of Florida

  Aug 2021 - Dec 2022

  Tools used:Python - NumPy, Pandas, Keras, Scikit-Learn, TensorFlow, Matplotlib, SeabornR - tidyverse (readr, dplyr, ggplot2, tidyr), caret, knitrMicrosoft suite, SAS, SQL, Tableau, Visio• Machine Learning Model using R for Federal client : Created classification model that predicts COVID-19’s impact on LILA communities in the USA with 78% accuracy.• Amazon analysis using R: Analysed factors impacting Amazon's fulfillment centers' location rationale using Kaggle data to run GLM regression.• Prediction Model using R: Predicting if poverty rate and vehicle access to supermarkets has an impact on SNAP benefits received by housing units in California state, using regression models.• Relational Database Management: Created relational database and logical schemas for an online tutoring business using SQL. Created Entity–relationship model for pet-sitting business using Visio.• Contract lists using Python: Created complex sales contract lists that used user inputs to calculate revenue & other variables and visualized results.• IMDb visual analytics using Tableau: Extracted and cleaned IMDb database. Performed visual analytics to solve business questions, made predictions using trends, and drew strategic insights that could help movie-makers.• COVID-19 Vaccine data analysis using SAS and SQL: Cleaned, manipulated, analysed, and visualised vaccine data to solve business questions regarding - vaccine brands comparison and quality across production lots. Show less

  • Student Assistant

    Mar 2022 - Dec 2022

  • Graduate Level Projects

    Aug 2021 - Dec 2022
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  CHRISTUS Health

  Feb 2023 - now

  IT Data Analyst 2

  • Developed and leading the maintenance of 4 interactive dashboards, offering senior management critical insights into Virtual Care services’ key KPI metrics such as staff utilization, clinical documentation, and patient volume.• Functioning as a validator for 3 system-level critical projects, that annually save the company over $5 million in government reimbursements and regulatory impact through informed decision-making.• Currently involved in a pivotal project to source raw data from the company's Data Lake, aiming to enhance data security and consistency while reducing dependency on external vendors.• Automated data validation processes, including accuracy and completeness checks, ensuring instantaneous identification and resolution of discrepancies, resulting in a significant time-saving equivalent to 1 FTE.• Collaborated with Subject Matter Experts (SMEs), data partners, and project sponsors, incorporating feedback to ensure project alignment with business goals and regulatory requirements. Show less