Adam Brownell

[2423 Federal Ave, Los Angeles, CA 90064]
(949) 350 0594 | adam1brownell@gmail.com

Education

University of California, Los Angeles

2014 - 2018

B.S.: Cognitive Science/Computation, minor in Digital Humanities

Relevant Coursework: Machine Learning, Machine Learning in Brain Science, Machine Learning in Bioinformatics, Research Statistics, Fundamentals of Artificial Intelligence, Algorithms & Complexity, Behavioral Neuroscience, Discrete Mathematics

Professional Experience

Retina.ai
Santa Monica, CA

Data Scientist
July 2018 - Present
  • Researched stronger time-series models and sequence forecasting through the use of recurrent nets (RNNs) and meta-learners
  • Produced email campaign success analytics in context of customer lifetime value (LTV) to provide vital insights to clients
  • Presented LTV elasticity concerns in Pareto family probabilistic models leading to improvements for both business intelligence and predictive power
  • Led team in the development of data-driven Virtual Assistant for clients, engineering the MVP locally before deployment to serverless framework for production

Textpert
Westwood, CA

Artificial Intelligence Engineer
Dec 2017 - June 2018
  • Conceptualized heat-map visualization for mid-layer output of convolutional nets (CNNs) to showcase model’s effectiveness and learnings about emotion expression
  • Implemented machine learning techniques (confusion matrices, validation sets, etc.) to previously implemented model to inform future architecture and hyperparameter decisions
  • Compiled and presented pre-VC acquisition report to inform business development

BCG Digital Ventures

Manhattan Beach, CA

Data Scientist
July 2017 – September 2017
  • Detected subtle emotions from phone calls for multiple Fortune-500 companies to better analyze over 100,000 daily customer service calls in real-time
  • Independently developed data analysis, visualization, and prediction pipeline leading up to important client meeting by utilizing various Python/R modules such as numpy, pandas, matplotlib, keras, scikit-learn, e1071, nnet, and glmnet
  • Applied agile development over a 10-week innovation sprint in order to produce the most effective machine learning models and preprocessing technique

Product Manager Intern
July 2017 – September 2017
  • Created product vision for client's investments by researching/validating product-market fit alongside outlining feature selection
  • Coordinated with design, engineer, and business analyst teams to test product feasibility and mitigate risks through careful structuring of MVP incubation plan and daily scrum meeting
  • Invited to present to client's executive board as a summer intern

Computational Vision and Learning (CVL) Labs
Westwood, CA

Research Assistant
Aug 2016 - July 2018
  • Constructed predictive Brain-Computer Interface models built upon classification algorithms found in tensorflow and scikit-learn
  • Scripted models of cognition by synthesizing Bayesian statistics and intuitive physics and working closely with domain experts
  • Designed behavioral experiments using pybox2D and Matlab to collect/analyze data for smarter cognitive models

Phoenix & Powell
Venice, CA

Lead Consultant
June 2017 - Aug 2017
  • Led team of student consultants to address product strategy, market analysis, and user research for client's product during project cycle
  • Worked intimately with LA-based start-up company and pushed MVP forward by verifying critical assumptions
  • Independently developed novel framework for start-up consulting and accelerated product roadmap results & promoted cohort cooperation. Framework adopted by consultancy and used in future project cycles
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