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Data Engineering

Berkeley, CA
March 18, 2020

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Moraldeepsingh Sachdeo

San Francisco Bay Area, CA +1-510-***-****

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University of California Berkeley (3.63/4) Aug 2019 - Dec 2020 Master of Engineering in Industrial Engineering and Operations Research Concentration: Data Analytics and Machine Learning Technical Coursework:

Applications of Data Analytics, Applied Data Science with Venture Applications (Data-X), Supply Chain Management, Optimization Analytics, Risk Modeling Simulation and Data Analysis, Industry Analysis Management Coursework [Haas School of Business]: Big Data and Better Decisions, Managing the New Product Development Vellore Institute of Technology, Vellore, India (9.11/10) 2014 - 2018 Bachelor of Technology in Mechanical Engineering Ranked top 5%in Cohort PROFESSIONAL EXPERIENCE

Beam Solutions, San Francisco Sept 2019 - May 2020 Data Science Intern & UC Berkeley Capstone Project Team Member

● Goal: Build Python-driven unsupervised machine learning models, to cluster client text data into interpretable groups that isolate and identify malicious or fraudulent financial activity

● Transformed corpus of project descriptions into model-ready summaries using NLTK and RegExp to lemmatize, stem, and translate text

● Researched and assessed the performance of pre trained word embeddings, including: Word2Vec, GloVe, and Facebook fastText, for clustering client text dataset into distinct categories

● Further Scope: Validate and integrate text embeddings with additional data features to identify cases of financial fraud Imarticus Learning, Mumbai, India Jan 2019 - July 2019 Data Analytics Trainee

● Collaborated with team members to gather data, Predict and increase Walk Ins by 47%which led to an increase in revenue by $5k

● Executed Machine Learning algorithms to classify the top 10%customers for selling product

● Assisted in creating and maintaining Tableau Dashboards presenting quarterly statistics to Management Board Mercedes Benz India Pvt Ltd, Pune, India Dec 2017 - Dec 2018 Operations Trainee

● Handled logistics and supply chain of Paint Shop for 4 variants of Mercedes Benz Cars (S, E, C, GLC)

● Identified Stations for process Improvement using SQL which lead to cost saving of minimum $15k annually

● Managed a team of 30 Members to perform mechanical operations on CKD Model of cars

● Presented 20 KPI Statistics- Key Performance Index charts for MB India

● Awarded Suggestion Award for improving the workplace efficiency and cycle time of stations by 6 minutes SOFTWARE SKILLS

● Programming Languages and Visualisations Softwares: SQL, Python, R Programming, Tableau

● Statistical Software: SAS Studio, Minitab, Free Mind

● Modeling and Algorithms: Machine Learning, Mathematical Modelling, Statistics, Risk Modelling, NLP PROJECTS

Credit Risk Analysis (Python)

● Built a predictive model with accuracy of 82.5% for the banking company by scoring the lender’s propensity to be a defaulter, and exploring the variables associated with it, helping them to build strategies. Validated the proposed model using Cross Validation

● Perform binary text classification on emails using Naive Bayes classifier and add-one smoothing

● Packages used: NumPy, Pandas, sklearn, matplotlib SMS Spam Classification (Python)

● Collaborated with a team of 5 to Perform binary text classification using Naive Bayes classifier and extracted features by vectorizing text

● Performed raw data processing: removed stop words, html tags and Implemented the spam classifier using logistic regression with accuracy above 90%

● Used confusion matrix as the measurement of the machine learning model Market Basket Analysis of Online Retail Data (R Programming)

● Wrangled through 500000+observations to perform MBA and find the underlying association rules contained within

● Identified target markets based on size, structure, quantity, and quality of the customers’ market basket to understand the pattern in which products are purchased

● Packages used: ggplot2, arules, arulesViz, tidyverse, dplyr, lubridate Development of Sustainable Value Stream Mapping for Unit Part Manufacturing: A Simulation Approach (VSM, SQL, ARENA) International Journal of Lean Six Sigma (Published Research Article ISSN: 2040-4166

● Analyzed the current state of methodology adopted in a bonnet manufacturing industry using SQL and ARENA and optimized the process by designing a future state map using simulation approach

● Interacted with various Stakeholders to identify concerns in the Manufacturing Industry

● Classified and eliminated bottlenecks with the help of various lean techniques and improved VSM efficiency by 18.18%

● Highlighted a contrast of present and past scenario to underscore the importance of using VSM with Arena Simulation LEADERSHIP & EXTRA-CURRICULAR ACTIVITIES

● UC Berkeley Master of Engineering Ambassador and Admissions Interviewer for the batch of 2021

● Technical Head, Youth Red Cross VIT, NGO (2017-18) Successfully handled 200+Blood donation cases in CMC Hospital, India

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