About me

While the terms “Data Science”, “Data Engineering” and “Big Data” remain hard to pin down exactly (even in 2020), I like sharing my thoughts and my ongoing learning by writing, coding, and exploring these fields with you here.

I’m Frank Fineis, an experienced Data Scientist, Data Engineer, Solution Architect, and statistics PhD student. Thoughts and opinions I express are none other than my own. Here is some of my background:

  • Lead Data Scientist at Uptake, a Chicago industrial internet of things SAAS firm. First task: real-time anomaly detection algorithm (hold a patent for this). Next tasks: building predictive failure models in R, prototyping applications with Shiny, building full-stack model performance tracking and NLP-based supervised label re-assignment automation platforms while managing a small, nimble team of rockstar data scientists and data engineers.
  • Computational Research Analyst at Northwestern’s Institute of Policy Research. I worked with Professor Larry Hedges to anonymize states’ department of education data for use by public research institutions.
  • Senior Consultant at Aptitive. Leading a team of SQL developers, we built an end-to-end cloud data platform and BI stack for a large North American logistics brokerage firm. AWS, Airflow, and Snowflake - this is how modern analytics platforms should work.
  • Statistics PhD candidate at Northwestern. Some of my varied research topics include…
    • Bioinformatics. Check out our open-sourced RNA-seq normalization tool called degnorm published in Genome Biology.
    • Deep learning. Working with LSTMs to predict nucleosome locations and another projected dedicated to detecting adversarial examples.
    • Mixture of experts models: did you know that radial basis function networks can be reformulated as a mixture of linear experts?
    • I TA the department’s Data Science course series.
  • DevOps consultant at Northwestern IT’s Research Computing Services. Dockerizing computing suites, stress testing our Linux HPC, and helping other researchers scale their work to the cloud.

Consulting

If you’re looking for an experienced data scientist, data engineer, or solution architect, then let’s chat.

  • SQL database development, optimization, and administration. PostgresSQL, Snowflake, MySQL, MS SQL Server, Oracle, all of it, any aspect.
  • Python code development and web dev. Need an experienced Flask developer?
  • Automation, containerization, and continuous integration needs.
  • Apache Airflow. Let’s get your Airflow deployment healthy, fast, and scalable. Custom Airflow integrations available. And if you’re new to Airflow, let me get you started.
  • Going to the cloud. AWS solutions for databases and data pipelining. Enable my Alexa skill, CTADelays.
  • Anything data science:
    • Dataset creation, validation, and standardization
    • Machine learning model development and deployment
    • Hands-on deep learning experience with Keras, PyTorch, Tensorflow
    • Timeseries forecasting
    • Time-to-event and customer churn models
  • Dashboarding and data visualization needs. No statistician would be worth anything without years’ worth of Tableau and open source data visualization experience.

Get in touch

Let’s work together.