CV/Resume

Work experience

i) June 2023 - September 2023:

• Data Scientist, NHS NORTHWEST AMBULANCE SERVICES, Manchester, UK
  • Predicted ambulance response time by implementing 3 random forest models for regression analysis and one classification model that achieved 94% accuracy. Created new statistical algorithms for ambulance demand density calculation, ensuring compliance with data governance.Utilized these insights to build a simulation model, optimizing dispatch center placements to achieve significant reductions in response times across targeted regions.
  • Collaborated with technical and non-technical stakeholders, such as Business Analysts, Data Analysts, PMO, and cross-functional teams, to gain domain expertise and understand the data, ensuring timely deliverables.

ii) June 2019 - September 2022

• Big Data Engineer, MAVERIC SYSTEMS, Bangalore, India
  • Client - Citibank North America
  • Spearheaded the implementation of a Kafka-Spark AWS Cloud data pipeline for Credit Card transactions, resulting in a notable 30% speed improvement crucial for real-time transaction analysis in the banking sector, while ensuring high code quality and adherence to departmental practices for efficient project management using Jira, earning recognition from the Director for outstanding performance.
  • Applied statistical methods such as regression analysis, correlation analysis, and NLP sentiment analysis to gain insights from large datasets, optimizing marketing strategies for enhanced business outcomes.

iii) June 2018 - September 2018

• Business Analyst Intern, Sable 37 , Dubai, UAE
  • Optimized PowerBI HR Dashboards, enhancing data interpretation and cross-functional collaboration.
  • Automated HR reports with advanced Excel, creating interactive dashboards, thereby boosting operational efficiency.

Education

• Masters in Data Science, Lancaster University, 2023
  • Coursework: Data Mining (Linear/Logistic), Data Science Fundamentals(hypothesis formulation, research findings implication, data processing, organisation results communication), R and Python Programming, Satistical Fundamentals (MLE and GLM’s), Statistical Foundations(Sampling uncertainty, Statistical inference, Model fitting), Advanced Machine Learning, Neural Networks & Deep Learning, Time Series Analysis, Data Visualization, Optimisation and heuristics.
• Bachelors of Engineering in Information Science Engineering, BMS College of Engineering, 2019
  • Coursework: Advanced SQL , C++, Java , Python, Excel

Skills

• Python
  • Pandas, NumPy, MatPlotLib, Seaborn, scikit-learn, scikit-surprise, SciPy, TensorFlow, Keras, NLTK, SpaCy, Spark, PyTorch,
• R
  • Markdown, dplry, ggplot2, tidyr, tseries, lmtest, forecast
• Big data
  • Apache KAFKA , Apache Hadoop , Apache PYspark , MongoDB, Cassandra,
• Machine learning model buidling
  • Supervised Learning, Unsupervised Learning, Model Evaluation, Model Deployment
• SQL
• Tableau
• PowerBI
• Excel
  • PivotTables and PivotCharts, Power Query, Power Pivot, Power View
• Data Analysis Exploratory Data Analysis, Data Cleaning, Data Manipulation, PLM, T-Tests, ANOVA, Chi-square tests, Feature Engineering
• Testing Functional testing, Unit testing
• Data Governance
  • Masking personally identifiable information (PII) by encryption, tokenization, data masking, access controls, and auditing
• Health Data
  • Thorough understanding of Electronic Health Records, SEIR Model , Infectious Disease Modeling, Epidemiology
• ETL Tools (TALEND)
• Project Mangement and Agile Methodology
  • KPI Tracking, JIRA, Github , Confluence