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Analyst
Deloitte• September 2016 - March 2021
ETL Tester (Informatica Intelligent Cloud Services, Informatica PowerCenter, PostgreSQL & MS Excel): · Designed and wrote 100+ test cases by referring user stories to test all conceivable positive and negative scenarios which avoided defects like data corruption or data loss · Developed 100+ SQL queries for each database related test scenario to verify if functions produce expected results for given inputs · Automated the ETL testing process by using VBA programming which reduced the manual effort by 70% · Proactively assisted my team lead and colleague in testing front-end functionalities on desktop and mobile devices (Perfecto) to ensure website’s presentation layer is bug-free ETL Developer (Informatica PowerCenter, Data Quality, Microsoft TFS & MS Excel): · Managed the application lifecycle report, Microsoft TFS (Team Foundation Server), to provide a comprehensive overview of the project's progress to the client and leaders · Developed 15+ ETL mappings using Informatica PowerCenter and Data Quality which provided formatted and qualified data for front-end use · Conducted data exploratory analysis on 10+ source files and discussed essential vs non-essential data with the client to achieve business objectives Programme Management Officer (MS Excel, MS PowerPoint & MS Visio): · Onboarded 150 resources for a project by closely working with client, offshore managers & leaders and coordinating with onshore colleagues, security, and third-party drug testing team to avoid delay in project kick-off · Raised and tracked 15+ client software requests for the workforce as per their role and followed-up with the client in case of a delay to ensure they hit the ground running · Created daily and weekly success reports by gathering data from 8 team-leads to deliver a clear picture of the project’s progress to the client and leaders
Education
University of Bath
Data Science, MS• October 2021 - October 2022
* Applied Data Science: Provided extensive hands‑on experience in practical data‑driven analytic science, from basic data handling, curation, cleaning, and pre‑processing through analysis. Projects include: – Weather visualization ‑ Used Pandas to parse the CSV files into an appropriate python data structure and Numpy to compute the minimum, maximum, mean and standard deviation for each component of the data to create 2 info‑graphics (monthly and seasonal) – Sentiment Analysis of Reviews ‑ Implemented NLP data wrangling methods by using uni‑gram, bi‑gram, tokenization, lemmatization & stemming and removed punctuation and stop‑words. Used Multinomial Naive Bayes model to train and test the dataset – Use Case 1: Data Protection as per GDPR UK ‑ Assessed the compliance of the company against the requirements of the GDPR UK (General Data Protection Regulations) as brought into law by the Data Protection Act 2018 by providing answers to a series of questions – Time diary data capture, analysis, and reporting ‑ Designed data collection form, implemented data wrangling methods and reported my analysis using an info‑graphic – Use Case 2: Electric Vehicle Support Infrastructure ‑ Implemented data wrangling methods and used ARIMA to analyse and forecast time series data * Statistics for Data Science: Basic theory of probability and statistics, and the ability to recognise when this theory can be applied * Machine Learning ‑ I: Algorithmic approaches to ML and an introduction to advanced topics such as probabilistic techniques. Projects include: – Data Exploration ‑ Explored data and derived my own algorithm for classifying – Decision Trees ‑ Implemented decision tree algorithm on a binary classification problem involving data manipulation/visualisation hyper‑parameter selection, recursion, and building a prediction model – Linear Regression ‑ Introduced to the TensorFlow toolkit and fundamental linear regression model from a number of different angles – Coffee Machine ‑ Implemented belief propagation to solve graphical model problems * Machine Learning ‑ II: The breadth of machine learning along with detailed treatment of advanced methods. Projects include: – Age estimation and gender classification ‑ Used Google Colab to build two CNNs (our own model and pre‑trained model) and compar the results – Sentiment Analysis ‑ Solved an NLP task related to sentiment analysis using support vector machines (SVM) and boosting techniques * Software Technologies for data science: Undertake lower‑level data science using Python and its associated libraries and to scale up an apply higher‑level software to ”Big Data”. Projects include: – Noughts and crosses ‑ Implemented a simple AI/recursive function that plays the game using Min‑max algorithm – Ray tracing ‑ Vectorized the code to write a simple ray‑tracer program along with using list comprehensions – Coffee Shop ‑ Used classes and implemented object oriented programming concepts to simulate a coffee shop – Search Engine ‑ Used string methods to create a search engine for recipes – SQL Databases ‑ Developed an SQL database for the student assessment by using Data Manipulation, Data Definition and Data Control Languages – Mini Project: Traffic Recording Application ‑ Understood the browser based front‑end that makes use of HTML, CSS and JavaScript and how it interacts with the server. Implemented a back‑end framework for the app written in Python using SQL * Research project preparation: Undertaking a primary research literature search, assessing the relevance of research publications, judging the quality of secondary research resources, such as web resources, critical analysis of research papers, writing a review of a research area, preparing a research proposal. – Dissertation title: Achieving geometric transformation of Euclidean representation derived from non‑Euclidean data by using Pix2Pix network
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