Liam Connell
Verified Expert in Engineering
Software Developer
Liam has 4 years experience in all things data, including data engineering roles, machine/deep learning projects, and the harnessing of the cloud computing tools. With those three pillars of data, he develops powerful tools that can be applied to either business processes, strategic decision making, or consumer products. Liam prides himself on strong two-way communication, alignment with client goals, and the highest standards.
Portfolio
Experience
Availability
Preferred Environment
Amazon Web Services (AWS), Terraform, Python, Git, OS X
The most amazing...
...thing I've coded is a variational auto-encoder that uses encoding gradients to generate synthetic data and computationally approximate the Wasserstein distance.
Work Experience
Machine Learning Engineer/Consultant
Boston Consulting Group
- Developed a scalable machine learning framework in order to deploy an automated analytics product, which was leveraged by other data scientists.
- Architected ML Pipeline that ingested, processed and modeled over a TB of data daily.
- Wrote a guide to best practices in developing scalable ML.
Data Engineer
Auth0
- Created an ML-based customer health score that was able to improve sales and customer success personnel allocation by 80%.
- Designed and developed an over-quota tracking process that drove a campaign to half a million dollars in increased ARR, 10% of the quarter’s ARR gains.
- Developed and maintained a Redshift data warehouse along the entire pipeline: Coordinating with other engineering teams for designing import processes; ETL design and implementation; Dimensional modeling; Coordinating with the business community to ensure effective use of the data warehouse; designing Machine Learning processes to aid in decision making and gain insights.
Experience
A Tour Through TensorFlow with Financial Data
https://liamconnell.github.io/jekyll/update/2016/07/18/a-tour-through-tensorflow-with-financial-data.htmlThis project has been very popular since it was released, especially since at the time of release (early 2016), TensorFlow was a new technology and tutorials had stayed comfortably in the sphere of toy implementations like MNIST digit recognition. I regularly responded to monthly emails from researchers attempting to replicate the code, many of whom were Ph.D. candidates themselves.
Skills
Languages
Python, SQL, R
Libraries/APIs
TensorFlow, NumPy, Scikit-learn, Keras, Pandas, PySpark, Spark ML
Storage
PostgreSQL, Redshift, MongoDB
Paradigms
ETL
Industry Expertise
Teaching
Other
Data Warehouse Design, Machine Learning, Data Warehousing, Online Tutoring, Deep Learning, Artificial Intelligence (AI), Generative Adversarial Networks (GANs), Variational Autoencoders, Image Recognition, AWS Cloud Architecture, Natural Language Processing (NLP), Predictive Modeling, Financial Modeling, Reinforcement Learning, Deep Reinforcement Learning, GPT, Generative Pre-trained Transformers (GPT)
Frameworks
Django, Django REST Framework
Tools
Git, Terraform, Apache Airflow
Platforms
OS X, Amazon Web Services (AWS), Azure, Google Cloud Platform (GCP)
Education
Bachelor's Degree in Mathematics
Colby College - Waterville, Maine
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