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David Samuel

Data Scientist

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About Me

Beginning my career as an infrastructure engineer, I honed my skills in project management, complex construction oversight, and the meticulous examination of engineering designs for cost and quality efficiency. Intrigued by the potential of technology, I initially dipped my toes into coding through the creation of straightforward games and applications. This nascent curiosity rapidly grew into a profound passion for computer science, data science, and product management. In pursuit of my passion, I joined a Master's program in Data Science, mastering concepts such as data structures, algorithms, data processing, software engineering economics, data value, and digital marketing. One of the milestones in my career was launching my first startup, MusicMind. In this venture, I spearheaded product design, database creation, team recruitment, and raised $40,000 in funding. Further demonstrating my entrepreneurial spirit, I developed a React.JS web app, designed as a live cryptocurrency price calculator. A deep love for data has consistently been the backbone of my professional journey, leading me to accumulate significant experience in building web crawlers, implementing security measures, overseeing DevOps, managing database access, as well as mining and parsing data from public APIs.

Experience

MindTree

Chief Technology Officer

  • Engineered a comprehensive webpage and integrated a robust intake management software for streamlined payments and scheduling. This strategic initiative bolstered operational efficiency for 75% of patient processes by 140%, halved IT-related costs from Q4 2022 to Q3 2023, and accelerated patient and provider acquisition by 2x and 3x, respectively.
  • Strategically developed a customer journey framework, constructed a comprehensive patient database, and implemented an effective acquisition strategy. Integrated multiple lead channels into patient funnels, resulting in an impressive conversion rate of pre-screened patients at an average of 40%.
  • Formalized and standardized patient screening procedures, providing pivotal consultation in developing an AI-assistant for handling pre-screening calls, which improved call handling efficiency and accuracy by an estimated 30%.

Edx

Data Analytics Instructor

  • Delivered comprehensive instruction to a class of 17 students across diverse subject areas, including Excel, Python, SQL, Tableau, statistics, and machine learning, consistently achieving an impressive weekly satisfaction rate of 90%.
  • Served as a mentor to four teams, fostering their analytical thinking skills and guiding the technical implementation of their exploratory data analysis reports.
  • Oversaw the technical upkeep of a substantial 1.5 GB repository on Github.com and Gitlab, a strategic move that effectively conserved approximately 5 hours of weekly code maintenance time.

Amazon

Data Analyst

  • Developed and optimized 5 Tableau dashboards, enabling real-time KPI visualization, and resulting in a 10% increase in data accessibility and decision-making speed across various business teams.
  • Collaborated with data engineering teams to discover and integrate 10 new data sources, enhancing the breadth and depth of organizational data by 25%, thereby optimizing data-driven insights.
  • Authored and presented 5 comprehensive data analysis reports to business stakeholders, informing strategic decisions and contributing to a 15% increase in operational efficiency.

T. Rowe Price

Data Analyst

  • Engineered advanced predictive models using Facebook Prophet, enhancing time-series forecasts accuracy for a large-scale contact center with 1,000+ employees and nearly 3 million annual calls. The newly implemented model achieved a significant 50% reduction in the mean absolute percentage error (MAPE) of long-term forecasting, translating to an annual saving of over $1.6M for workforce management.
  • Led the development of data analysis reports, dynamic Tableau dashboards, and Python notebooks, providing critical analytics insight to an organization comprising over 200 managers and executives. This effort formed the backbone of the organization's data-driven approach, influencing and driving 80% of all analytical insight and strategic decision-making.
  • Successfully mentored and managed a new data analyst, overseeing their development of 5+ key projects which increased team efficiency by 20%, while fostering their professional growth which led to a 30% improvement in their data analysis proficiency within a six-month period.

Thinkful

Data Science Instructor

  • Directed numerous recruiting workshops, achieving a 33% sign-up rate conversion and conducted over 100 data science code reviews, offering indispensable feedback to students from prominent companies like HBO and Yelp.
  • Rendered expert mentorship to a student on feature engineering, utilizing real estate data to forecast political preferences based on physical attributes such as building materials, square footage, and garage count.
  • Assessed Data Science Bootcamp students during mock interviews, probing knowledge in data analysis, experimental design, supervised and unsupervised machine learning, along with behavioral competency.

Google

Machine Learning Instructor

  • Partnered with an interdisciplinary group of Google Engineers, Managers, and University Professors to develop and deliver rich educational content covering Statistics, Neural Networks, and Computer Vision. This pivotal role included detailed planning and lecture development for Google's 10-week Applied Machine Learning Intensive Summer 2019 cohort, contributing to a 30% increase in student comprehension and hands-on proficiency.
  • Actively provided mentorship and executed meticulous code reviews for four distinct teams that successfully deployed deep learning applications. One standout project involved the use of PyTorch to train and deploy a robust image classification model, capable of accurately distinguishing between recyclables and non-recyclables, thereby improving model precision by 25%.

Platform.ai

Machine Learning Engineer

  • Leveraged Fastai library on Google Cloud Platform, developing a SoTA computer vision model for 7-way room type classification, boosting test set accuracy from 91% to a stellar 98%.
  • Harvested 19,000 of Redfin’s latest public listings, compiling a 50GB dataset with over 350,000 images and annotations, significantly enhancing the validation process for our image classification model.

Education

Southern Methodist University

Jan 2016 - Aug 2017

Master of Science in Data Science

While attending SMU's online Data Science Master's program, I worked with professionals from various industries and companies including Apple, IBM, and Microsoft. I did research into statistical analysis, machine learning algorithms, network engineering, and computer science principles.

University of Massachusetts

Sept 2005 - May 2009

Bachelor of Science in Civil Engineering

Projects

redfin images

Predicting Rich Attributes in Real Estate Images​

Built a web crawler to capture images and metadata from Redfin.com’s newest listings, and developed a few-shot model for predicting property attributes like pool, view, kitchen island, high ceilings, hardwood floors, and fireplace.

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kickstarter

Kickstarter: Predicting Success

This project takes a dataset of over 300,000 Kickstarter projects from 2009 to 2016. Data is cleaned, analyzed, visualized, and prepared for modeling using Multiple Linear Regression to predict the amount pledged for any particular kickstarter.

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spotify

Spotify Analysis

An exploratory data analysis project that aims to understand the highest volume streaming music on Spotify in 2017

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CryptoBox

CryptoBox

CryptoBox brings cryptocurrency to the cloud, and currently offers a Price Ticker & Currency Calculator that helps you manage your cryptocurrency. The calculator allows you to simulate trades & token exchanges.

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musicmind

MusicMind

MusicMind is a Music Messenger App and Social Network that allows users to connect to their personal music collection or music streaming service, such as their Spotify account. They can then stream songs, and curate and share music video messages to the network, or to other social media platforms. MusicMind has a Database that holds and collects lyrics and other types of music metadata suchch as artist popularity, and audio-analysis features. We are using music metadata, and lyrics to transform songs into visual augmentation, creating a multi-media experience for users to engage more with music in real-time.

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twitter

Natural Language Processing using live Twitter data

This report dives into the process of collecting and analyzing tweets from Twitter's public API. The project details the use of Spark, and nlp library to discover tweets, determine context, and filter topics. As a result of this project, my team was able to analyze thousands of tweets leading up to the 2016 NBA Finals to predict the winner, The Golden State Warriors.

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facial image analysis

Facial Image Emotional Analysis using Microsoft Cognitive Service

This report was written with a team of peers from SMU in 2016. It covers data collection, analysis and reporting on how public images of the presidential candidates affected their polling numbers on a weekly basis.

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mnist

Classification of MNIST Digits with Keras

This Jupyter notebook was developed by myself demonstrates the power of python, SK-learn, and Keras (runs on TensorFlow) to to get a 99.54% accuracy on kaggle for top 18% of submissions.

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clustering

Survey of Bitcoin, Ethereum, and the future of blockchain

This report was written by myself for a Network Security Class in 2016. It provides a survey of blockchain technology, and it's potential impact on banking, finance, privacy and democracy.

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texture map

Analysis of Wikipedia Perceptions

This report was written for SMU statistical Analysis in 2016. It details the relationship and significance of student and instructor perceptions and use of wikipedia for academia.

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Skills

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