Software Engineer-Other - Advanced
The Judge Group Inc.

Location: Coppell, TX
Description: Our client is currently seeking a Software Engineer-Other - Advanced

Summary:

Energetic data scientist who enjoys team environments, data engineering, and integrating artificial intelligence. With 6 yrs. of AI + data science projects under Superior Data Science LLC, Citigroup Data Science, Bell Helicopter Data Science and UTSW Neuroscience. I'm a Data Scientist who completed a Masters in Engineering and currently working on my MBA Frameworks and Libraries:

SQL Server, python, ETL pipelines, async python, multiprocessing, TensorFlow, Keras, object-oriented programming, NumPy, scikit-learn, Pandas, docker, CICD pipelines, flask server, bootstrap, JavaScript, CSS, advanced BASH scripting, Linux, microservices, gRPC, hashing, serialization, MLOps, Dev-ops, Kubernetes, git, MySQL, android studio, angular, Ubuntu, Windows, statistics, combinations, permutations, Itertools, finance, business

Education:

•Masters in Bioengineering with focus in Artificial Intelligence and Image Processing

•MBA and MS Finance Candidacies

•Graduate Courses: Advanced Machine Learning (PhD Course) - Neural Networks - Statistical pattern recognition - Digital signal processing, Image Processing

Projects:

•Convolutional Neural Network - Image Recognition Point of Sales Addition

•Convolutional Neural Network for an image recognition task for better POS efficiency in a heavy use environment

•Led project + debugged TensorFlow backend and [signature pad, http requests] JavaScript frontend code on a milestone basis for client

•Recurrent Neural Network - Stock Market Pattern Prediction

•TensorFlow recurrent neural network that trained on real stock market candle objects for pattern prediction

•Led project + debugged TensorFlow backend and [cross filter, d3 and angular] JavaScript frontend code on a milestone basis for client

•Deep Reinforcement learning stock predictor (reinforcement learning)

•Deep q learning using a convolutional neural network based on paper 'Playing Atari with Deep Reinforcement learning'

•Used TensorFlow for neural network layer construction

•Training a Smart Cab to Drive (reinforcement learning)

•Trained a cab to drive in a city simulation - by manually coding the agent with q learning concepts - using object-oriented python

Customer segmentation (unsupervised learning):

❖Used PCA analysis for dimension reduction and grouping

❖Sharpened logistical and statistical insight using matplotlib and pandas on the customer dataset

❖Predicting Boston Housing Prices (supervised learning)

❖Predicted Boston housing prices using past data to create a machine learning model using Python and NumPy databases

❖Decision Tree regressor, analysis of few decision tree models, analysis for overfitting and underfitting in model, conducted statistical analysis

Relevant Experience:

Sr. Data Scientist

Providing AI solutions using hums data, analysis and helicopters. Trend detection, anomaly detection, fault classification. Analysis of vibration data, heavy usage of signal processing and data engineering etc. pipelines All anomaly detection use cases below pertain to helicopter health analytics

1.Built Generative Adversarial model for anomaly detection

2.Built Ganomaly model for anomaly detection

3.Built Autoencoder for anomaly detection

4.Built Vanilla Artificial Neural Network for anomaly detection

5.Built Gaussian Mixture Model for anomaly detection

6.Automated hyperparameter testing with itertools (pipeline can test 100s models in one go)

Technologies used were TensorFlow, keras, azure (docker containers), scikit learn, and tons of python libraries to implement machine learning in a distributed containerized fashion. Also completed projects within a Jira Agile Methodology system.

Sr. Data Scientist

Worked on and near test and production servers regarding newly installed hbase, hive, Hadoop, Spark

1.Developed architecture and completed build with team for a high quality and Google tested, ai Citi cards recommender microservice

2.Educated team on AI and machine learning; Conducted Sprint agile methodology for AI project and acted as scrum master

3.Trained and Developed Google's wide and deep recommender using tf.estimator; Exported and used tf inference serialized model in flask server

4.Bootstrapped Flask server microservice for credit card recommendation service

5.Made TensorFlow model production ready: successful inference calls on protocol buffer TensorFlow using bytelist, tf.feature, tf.features and tf.example-

Data Science and Project Management Contractor Created Legal Structure for Data Science Consultancy and have been serving through C2C and freelancing contracts

1.Dr. Haven (Psychology) Chatbot: Chatbot forum to study data which could assist consumers directly without having research through the forums.

2.Stock Market Patter Classification: Recurrent neural network and flask server with crossfilter.js and other bootstrap modalities for an algorithmic trading platform

3.Trend Detection in Time Series: Linear regression trend detection with analysis of bias and variance

4.Hand Writing Recognition for Restaurant: For German restaurant which needed mobile app with recurrent neural network handwriting recognition

5.Recommendation Engine: singular value decomposition used to understand high correlation between products and consumers for ecommerce company

6.Kubeflow: Kubernetes and TensorFlow platform for containerized machine learning and production utilized for client with google cloud. Other google cloud technologies: firebase, big query, CICD pipeline, cloud run, bitbucket

Contact: gdavis@judge.com

This job and many more are available through The Judge Group. Find us on the web at www.judge.com

This job has expired.