Pranjal Shukla

Learning is my passion, so is the interaction of technology with product strategy.
@pranjalshukla98

Hi, I’m Pranjal, a Business Data Scientist with a Master of Science in Business Analytics from George Washington University. Skilled in SQL, Python, Databricks, and AWS with a record of enhancing data driven decision making and operational efficiency across healthcare, environmental, and fintech sectors

Skills

Programming: Python (Pandas, PySpark, Numpy, TensorFlow, Keras, pytorch, Scikit-learn), SQL, R
Databases & Bigdata : AWS (Data lakes Redshift), Databricks, Snowflake, Microsoft SQL Server
Tools & Platforms : JIRA, Azure DevOps, Tableau, Linux, Git, Docker
Machine Learning & Analytics: Linear & Logistic Regression, Decision Tree, Random Forest, SVM, K-Means, Gradient Boosting, CNN, ANN, LSTM, Time Series Forecasting (ARIMA), Predictive Modeling, NLTK, BERT
Core Competency: Business Operation, Process Improvement, Predictive Modeling, Technical Documentation, Product Analytics, Data Analytics, Data Mining, Data Visualization (Matplotlib, Seaborn, Plotly, Tableau), Data Modeling, Machine Learning, Statistical Analysis, Agile Methodology

Experience

Project Insulin

Data Analyst (Mar'24 - Present)                                           Rhode Island, United States
  • Utilized AWS Redshift, Python, and PowerBI to manage large-scale data analysis projects, enhancing process improvement by 12% and substantiating GTM analytics knowledge base that increased team efficiency by 10%
  • Conducted user acceptance testing (UAT) to ensure regulatory output compliance and data processing accuracy for reliable healthcare solutions.
  • Utilized P-value and Z-test statistical techniques to research and understand customer behavior, driving decision-making and business strategies.

    • World Wildlife Fund

    Data Analyst Consultant (Capstone) (Sept'23 - Dec'23')                     Washington DC, United States
  • AI Chatbot Modeling: Spearheaded the development of an AI chatbot leveraging NLP and LLM technologies, enhancing digital engagement by 35% through improved data governance and user interaction capabilities at the World Wildlife Fund
  • Implemented a RAKE (Rapid Automatic Keyword Extraction) based semantic search mechanism within the chatbot, achieving an 88% accuracy rate in keyword-driven queries, significantly enhancing user experience and search efficiency.
  • Enhanced performance by implementing QA pair storage & context-focused guardrails, saving $82K in costs.

    • DataLink Software

    Business Analyst Intern (May'23 - Aug '23')                                           Tempa, Florida
  • Led successful utilization of the in-house health intelligence tool, driving 30% increase in data-driven decision making in a span of 12 weeks
  • Project management: Managed and successfully delivered 4 client feature enhancement requests using Azure DevOps, ensuring transparent and timely communication throughout the project lifecycle
  • Built 10 BI dashboards using Tableau, transforming complex data into actionable insights for stakeholders, which improved decision-making processes.
  • Optimized Databricks Spark SQL queries, achieving a 50% reduction in query execution times
  • Partnership and Collaboration: Partnered with project managers & key stakeholders to identify gaps in business requirements and problems, translating 75 business use cases to feature specifications on JIRA, increasing project efficiency by 25% for Q3 2023.
  • User Engagement Enhancement and Advanced Analytics: Conducted SQL-based A/B Testing and implemented tableau dashboard for graphical representation features, refining metrics and documentation for product features to influence strategic decisions in Evoke360 (data-driven platform for value-based care), leading to 15 new user interaction metrics, significantly boosting user engagement and satisfaction.

    • Intellexs Investment Solutions

    Technical Associate (Jun'20 - Aug '22')                                                 Noida, India
  • Performed testing and analysis in Tableau integrated with python code of data collected from pipelines saving 30mins per operation cycle
  • Developed operational process flow for analyzing transaction processing of 6 client cloud accounts
  • Configured a medallion architecture ETL pipeline in Databricks using Spark SQL, reducing 15 hours of manual work per week and enhancing efficiency.
  • ETL Development: Implemented comprehensive ETL processes using Snowflake, establishing robust data pipelines from diverse sources to a centralized data warehouse, improving data accuracy by 13% and reducing manual data entry errors by 30%.
  • Analytics Framework Development: Established a data analytics framework utilizing Amazon S3, Glue, and Lambda to enable faster retrieval of key performance indicators (KPI), significantly reducing operational costs.
  • Deployed & devised an AWS Aurora SQL database solution, consolidating complex financial datasets for efficient analysis and reporting capabilities.

    • HCL Technologies

    Data Analyst Intern (May'19 - July'19)                                                 Noida, India
  • Performed predictive statistical analysis using ML algorithms by extracting e-commerce data through automated APIs from Amazon Redshift for AT&T to accurately forecast marketing campaigns that boosted revenue by 2%
  • Developed EDA (Exploratory data analysis) and feature engineering pipelines for Telecom dataset with 45+ features using Python
  • Instrumented & deployed product features using A/B testing technique, increasing visitors engaging with products by 20%