Jared Cameron Stanley, Developer in Denver, CO, United States
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Jared Cameron Stanley

Verified Expert  in Engineering

Bio

Jared has 10+ years of experience in data science, analytics, and machine learning, serving a wide range of clients, from startups to Fortune 500 companies. He's a former founder and holds a M.Sc. in applied physics. His projects include uplift marketing models driving 9%+ lift for 100+ million customers, big data analytics reducing $10+ million in annual OpEx, automated collectible appraisal using computer vision, autonomous drones, and $1+ billion climate resiliency planning.

Portfolio

Adinkra Inc.
Deep Learning, Machine Learning, Python, Artificial Intelligence (AI)...
Guidehouse
SQL, Spark, R, Python, Artificial Intelligence (AI), Data Engineering...
PwC
SQL, Python, Apache Airflow, MemSQL, Analytics, Data Science, Machine Learning...

Experience

  • Data Analytics - 11 years
  • Python - 11 years
  • Data Science - 11 years
  • Deep Learning - 8 years
  • Machine Learning - 8 years
  • Artificial Intelligence (AI) - 8 years
  • SQL - 7 years

Availability

Full-time

Preferred Environment

Deep Learning, Python, Spark, Machine Learning, Computer Vision, Artificial Intelligence (AI), Data Science, Analytics, Big Data, SQL

The most amazing...

...model I've built allowed us to rapidly distribute millions of vaccines during the pandemic to thousands of locations.

Work Experience

Founder & CEO

2020 - 2024
Adinkra Inc.
  • Grew and managed a team of 10+ analytics, engineering, marketing, and administrative staff to develop AI, data science, and machine learning solutions for clients in the healthcare, defense, and energy industries.
  • Built an autonomous drone, complete with custom navigation, perception, control, and end-to-end simulation tools. Demonstrated real-world solutions for major defense companies and helped clients secure $10+ million in funding.
  • Created an AI application for warehouse monitoring, including tools for data annotation, active learning, synthetic data generation, and edge deployment. Deployed to 1,000+ sites with estimated savings in the millions/year for operators.
  • Developed a disease outbreak model, patient marketing optimization model, and COVID-19 distribution optimization model for a large US retailer. These models impacted over 100+ million customers and 10,000 stores daily.
  • Created a big data solution for wind turbines and then used this to develop a yaw alignment optimization algorithm deployed to 1,000+ turbines, which saves $10M+ annually in OpEx.
Technologies: Deep Learning, Machine Learning, Python, Artificial Intelligence (AI), Software Development, Data Science, Computer Vision, SQL, Data Analytics, PySpark

Senior Data Scientist

2019 - 2020
Guidehouse
  • Built a state-wide grid risk model to inform over $1 billion in grid resiliency planning. This included weather modeling, asset risk modeling, graph analytics, and ingestion of processing of thousands of engineering and business documents.
  • Led big data proof-of-concept using Spark, R, and Scala to manage TB of streaming data. This included a robust standard error package in Spark, dynamic time-warping machine learning tools for customer segmentation, and Spark transformation pipelines.
  • Built a traffic accident risk model to support CapEx planning for Hawaii utility using road, weather, utility, and traffic data.
  • Spearheaded the development of an internal weather package to process NOAA data for firm-wide projects. Created FlexDash and Shiny dashboards and parameterized QC memos to visualize data and assess completeness.
  • Served as a lead modeler of the Bass diffusion model for forecasting electric vehicle (EV) adoption and EV siting analysis. Applied linear programming and optimization techniques to improve analysis times by over 200%.
  • Created a model to predict window stock, turnover, and efficiency changes in the United States using Bayesian inference. The automated approach allowed us to decrease client costs for the project by around 40%.
Technologies: SQL, Spark, R, Python, Artificial Intelligence (AI), Data Engineering, Software Development, Computer Vision, Data Science, Deep Learning, Machine Learning, Data Analytics, PySpark

Data Engineer

2019 - 2019
PwC
  • Architected the enterprise ETL solution to extract data from data lakes and major ERPs, process it using ephemeral MemSQL clusters, and update data warehouses. Included REST APIs, Airflow, and Dynamic SQL.
  • Developed a custom QC and testing suite in Python to perform regression, integration, and unit testing. Quality checks and Type 2 tracking ensured the highest data integrity.
  • Developed process mining and outlier analysis tools, including custom dashboards using D3 and Zoom.
Technologies: SQL, Python, Apache Airflow, MemSQL, Analytics, Data Science, Machine Learning, Data Analytics

Software Engineer

2018 - 2018
Payger
  • Delivered a block explorer REST application for real-time transaction monitoring of the Bitshares network.
  • Developed a blockchain payments platform on the Bitshares network to reduce transaction settlement times by over 10x compared to banks.
  • Designed an Elasticsearch back end and micro-service architecture using Java and AWS for data management and processing.
Technologies: Java, Amazon Web Services (AWS), Elasticsearch, Kibana, Log4j, REST, Python, Machine Learning

Graduate Researcher

2016 - 2018
TUM
  • Developed an AI-based approach to solar material discovery and optimization. Developed an end-to-end solution for creating simulated data and iteratively improving the model. Presented and published work at several conferences.
  • Worked at the Walter Schottky Institute and developed custom imaging, computer vision, and software analysis solutions to create new photovoltaic systems.
  • Worked at the Max Planck Institute for plasma physics on optical system development for the Tokamak fusion system. Wrote custom software to automate experiment analysis and fit physics-based models to optical data.
Technologies: Data Science, Artificial Intelligence (AI), Product Development, Data Engineering, Software, Computer Vision, Deep Learning, Python, Machine Learning, Robotics, Data Analytics

Product Development Consultant

2017 - 2017
Motius
  • Hosted design thinking and technology deep-dive workshops with several global engineering firms in electrification, virtual power plants, and blockchain. Develop technical roadmaps for new solutions in these spaces.
  • Created consumer technology products requiring custom PCBs, app development, data analysis, and CAD.
  • Developed internal resources and tools for growing tech startups, mainly focused on internal innovation incentives.
Technologies: Product Development, Blockchain, Renewable Energy, Electrical Engineering, Robotics, Python, Machine Learning

Professional Research Assistant

2014 - 2016
Laboratory for Atmospheric and Space Physics
  • Developed lunar dust and mass spectrometer models to process millions of image-charge signals for the LADEE lunar mission. Presented work at AGU 2015.
  • Developed image processing tools in IDL and Swift for dust accelerator calibration experiments.
  • Led the development of the SUDA mass spectrometer lab prototype for Europa's Clipper mission. Worked across science, engineering, and simulation groups to fabricate mechanical and electrical components and construct a working device for under $10,000.
Technologies: Swift, IDL, CAD, Electrical Engineering, Data Science, Machine Learning, Simulations, Computer Vision, Python, Artificial Intelligence (AI), Robotics, Data Analytics

Machine Learning Perovskites

https://github.com/jstanai/Machine-Learning-Perovskite-Properties-for-Photovoltaics
This was my thesis work, creating a novel approach to property prediction for photovoltaics. The work has been published in Advanced Theory and Simulation and featured by Synopsys. The tool kit allows researchers and developers to easily schedule large quantum simulation jobs on a cluster and extract key results for material science applications.

Tidyspark

https://github.com/danzafar/tidyspark
I helped contribute to an open-source project, "tidyspark," which provides an R interface for running Spark. This interface offers tidy functionality and syntax to the SparkR back end, allowing a cleaner and more useable method for bringing Spark into data science applications with R.

Movie Rental Application

https://github.com/jstanai/Video-Rental-Application
I developed a RESTful movie rental application in Node.js complete with user authentication, a MongoDB back end, request validation and modeling, and a testing framework. The goal was to gain experience building all aspects of an application in a new language.
2016 - 2018

Master of Science Degree in Applied and Engineering Physics

Technical University of Munich - Munich, Germany

2011 - 2015

Bachelor of Arts Degree in Physics (Minor in Mathematics)

University of Colorado Boulder - Boulder, Colorado, USA

FEBRUARY 2019 - PRESENT

Deep Learning Specialization

Coursera

DECEMBER 2018 - PRESENT

The Complete Node.js Course

Code With Mosh

DECEMBER 2018 - PRESENT

UC San Diego Big Data Specialization

Coursera

Libraries/APIs

PySpark, TensorFlow, Keras, REST APIs, SpaCy, OpenCV, Pandas, NumPy, Scikit-learn, PyTorch, Node.js

Tools

Git, Plotly, GitHub, Apache Airflow, sparklyr, Jupyter, Kibana, CAD

Languages

Python, SQL, R, Markdown, Java

Frameworks

Spark, RStudio Shiny, Apache Spark, Hadoop, Flask

Paradigms

Anomaly Detection, REST

Platforms

Jupyter Notebook, MacOS, Windows, Visual Studio Code (VS Code), RStudio, Docker, Blockchain, Amazon Web Services (AWS)

Industry Expertise

Project Management

Storage

MongoDB, Elasticsearch, MemSQL

Other

Data Science, Machine Learning, Consulting, Deep Learning, Computer Vision, Artificial Intelligence (AI), Robotics, Modeling, Mathematics, Research, Convolutional Neural Networks (CNNs), Natural Language Processing (NLP), Recurrent Neural Networks (RNNs), MLflow, Data Engineering, Data Analytics, Data Visualization, AI Design, Deep Neural Networks (DNNs), Computer Vision Algorithms, Neural Networks, Generative Pre-trained Transformers (GPT), Statistical Modeling, Statistics, Big Data, EOS, Bayesian Statistics, Software Development, Analytics, Product Development, Software, Renewable Energy, Electrical Engineering, Log4j, Simulations, Web Applications

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