Data Science Machine Learning

Sam Black

New York, NY **********@*****.*** 551-***-**** https://sam-black.medium.com https://github.com/onesamblack

Summary

Highly accomplished data science leader and polyglot engineer with nearly a decade of experience building and growing data science teams, developing and deploying machine learning algorithms, data pipelines, and data warehouses across diverse industries, including financial services, management consulting, consumer web startups, real estate, and civic organizations. A certified cloud architect and hands-on software engineer proficient in Python, SQL, and Go, and experienced in managing DevOps on Amazon Web Services, Microsoft Azure, and Google Cloud Platform

Skills

Python, SQL, Go, Machine Learning, Deep Learning, Reinforcement Learning, Data Science, Data Engineering, Statistics, Causal Analysis, DevOps, Amazon Web Services, Google Cloud Platform, Microsoft Azure

Education

PhD Physics, The City University of New York

New York, NY June 2018 – June 2023

Dissertation research focused on Information Entropy in relation to Quantum Gravity

B.S. Finance, The University of Texas at Dallas

Dallas, TX September 2006 – June 2010

Professional Experience

Head of AI, Radiance

New York, NY December 2023 – Current

Developed the core product using custom diffusion models and deep learning on 3D and 2D mammogram data

Led the company through funding rounds, leading to acceptance into NVIDIA’s startup incubator and a successful venture backed round of $1.5M

Data Engineer, RXR Realty/View Inc.

New York, NY December 2020 – November 2022

Led a team of six offshore developers to redesign the backend infrastructure of the Worxwell platform which supports 10,000 IoT sensors and contained 27,000 lines of legacy code

Managed the company's operations across two cloud service providers, redesigned existing services and implemented automated CI/CD, reducing cloud computing costs by $81,000 annually

Launched Airflow to improve the company’s error-prone ETL processes

Created docker based templates for application code and an automated DevOps process that supports both Python, JavaScript and Go based data workflows

Designed a distributed mobile access control integration capable of handling 6k messages per second using a rest web service, message queuing and data storage using Go + Python

Developed core Python utilities which streamline common interactions with Google Analytics, AWS, Azure, Airflow, SQL Server and Postgres

Founder, Luminary Ltd.

New York, NY October 2019 – December 2020

Self-financed the entire company as a Cayman Limited Fund and managed all aspects of fund creation, legal, branding, and offshore funds management

Trained neural networks with PyTorch to mimic day traders using policy gradient methods which reached win-rates of 80% in offline market simulations

Wrote the entire platform using an architecture composed of Python based microservices to handle real time market data collection and storage, agent training and performance monitoring, agent simulation, agent deployment, trade execution and account management

Senior Manager, Cognizant

New York, NY December 2018 – October 2019

Worked with Credit Suisse Wealth and Asset Management as a Senior Data Scientist Manager and subject matter expert to develop a new data science group

Developed a product recommendation engine using methods derived from natural language models that achieved 90% accuracy for the bank's fixed income division

Worked with the operations team to deploy models to production and set up routine monitoring and maintenance. Production models directly contributed to $50M in monthly sales

Led a team of data scientists to train and deploy deep learning models (LSTMs) that forecasted asset inventory levels, reducing counterparty risk and funds availability

Worked with junior data scientists to analyze and publish research on initial public offerings (IPO) using statistical analysis, causal methods and data visualizations that gained high visibility and acclaim from Credit Suisse's executive office

Regularly led sessions to share best practices and train data scientists across the company

Manager, EY

New York, NY February 2017 – December 2018

Performed statistical analysis of email traffic within banking operations to understand information propagation and operational efficiency

Trained NLP models to understand message context and designed an automation software-as-a-service product which generated over $500k in revenue

Developed an anomaly detection framework for cybersecurity insider threat detection using machine learning based methods (LSTMs)

Created a go-to-market partnership with Splunk and drove marketing conversations with large financial institutions

Designed a conversational intelligence product using a microservice based architecture and NLP based models. Used to convert internal messages into a conversation graph used to identify trends, topics, and barriers to information flow

Developed a partnership with Microsoft Workplace Analytics and worked with a top US bank to deploy a proof of concept

Served as the group's lead technical developer, managing the infrastructure and DevOps for 2-3 node research clusters and databases

Worked to debug core NVIDIA GPU optimizations to speed up model training

Gave speeches/presentations to large audiences as part of EY’s Innovation Center, highlighting various Artificial Intelligence research projects and educating clients on use, contributing to sales opportunities

Freelance Data Scientist, Self Employed

New York, NY April 2016 – February 2017

Developed a frequent itemset mining model for an e-commerce company in Thailand

Developed a proof of concept and worked with the company to integrate into core business operations

Built a recommender engine using a hybrid collaborative filtering model for a company in Asia

Chief Technology Officer, Fynd

Los Angeles, CA October 2015 – March 2016

Served as the startup’s initial head of engineering, played significant roles in business strategy and product management, fund-raising, legal and operations

Developed the beta version of the product using Python + Django, Nginx, Postgres, Ansible and Jenkins CI for automated testing and deployment

Designed the core product recommendation algorithm using a custom scoring framework

Software Engineer, The Groundwork

New York, NY October 2014 – April 2015

Managed relationships with external partners, sourced engineering candidates, developed software architecture and analytical tools to achieve the group's objectives, eventually becoming the primary technology platform for Hilary for America

Created an auto-scaling data pipeline capable of processing and integrating terabyte scale unstructured data from a large number of distributed producers

Created data integration channels from internally developed microservices to external vendors and data integration via AWS Redshift

Senior Consultant, EY

New York, NY February 2013 – August 2014

Served as lead data scientist on an internal engagement to solve problems faced by the organization’s Global Technology Services team, performed statistical tests and causal analysis on large datasets including ANOVA, t-tests, chi squared tests for root cause analysis

Led a team of five senior analysts to perform detailed data quality analysis and develop automated testing procedures (T-SQL) for a major US bank as part of a regulatory order from the CFPB, which directly led to an additional $1.5M of add on engagement revenue

Designed a methodology for AML transaction monitoring, customer segmentation and alert threshold setting for a large US financial institution in response to a regulatory order which included custom development of statistical tests on large datasets using SAS, developed custom SAS modules to create conditional inference trees

Developed an NLP framework for Python used to determine the regulatory nature of customer complaints

Senior Analytics Consultant, JPMorgan Chase

New York, NY June 2011 – Feb 2013

Served as primary analytics lead on a number of business process improvement/six sigma engagements for Chase’s retail and transaction processing units

Developed a regression model trained on 20 million transactions and designed an operational process improvement in coordination with senior level managers and regulatory compliance which led to over $1.2 million in cost savings

Drove implementation of a for ATM claims operations that automates claim decision making, providing over $300,000 in cost savings

Operations Analyst, JPMorgan Chase

New York, NY June 2011 – Feb 2013

Used statistical process control to develop risk indicators for operations management

Co-created an operational risk index with Protiviti which gained industry recognition

Led a team to close control gaps across 2 internal lines of business during a critical regulatory risk event and laid the foundation for a firm wide standard in executing sworn statements

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