Solomon Kahn

Founder & CEO at Delivery Layer | ex Nielsen P&L owner | ex unicorn SaaS VP of Data | Host of the Data That Drives Revenue Podcast

I'm a long-time data leader, currently leading ReportingApplications.com, a consulting company focused on building - you guessed it - Reporting Applications.

Why Reporting Applications?

Because they’re tricky to build in ways that most companies don’t realize until they are live with customers and dealing with unexpected business problems.

We believe there’s an art to building great reporting applications, but not many people have focused on this area deeply enough to become experts.

By working with us you can benefit from our many years of lessons learned.

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Prior to starting ReportingApplications.com I was the founder of Delivery Layer - a SaaS product that powered customer facing reporting applications.

Before that I was VP of Data Strategy at Helium 10 where I led all things data (Data Engineering, Data Science, Data Product Development and Analytics). I previously ran product & analytics with P&L responsibility for Nielsen Sports, the global leader in Sports Sponsorship data.
  
Early in my career I ended up with the mix of statistical, business analysis and programming skills that would turn into the ideal background for a data scientist. Since then, I've been leading data teams, building data products and running data businesses.

My philosophy is that data isn't the hero - it's the sidekick. It's only valuable if it improves the lives of your customers, or helps someone make better decisions.

Get in touch if you need to build a reporting application!

And connect and follow along for lots of content around data leadership, becoming a better data person, and (of course) Reporting Applications.

Founder & CEO

Delivery Layer is a platform that powers revenue generating data through web applications and APIs that deliver your internal data to customers and partners.  
  
We dramatically improve time to market for data products. Enterprise scale products can launch in under a quarter, and consulting project front-ends can ship in days.  

This is only possible because we focus exclusively on applications that deliver your internal data to customers (as opposed to when customers send data into your systems).
  
Our pre-built infrastructure and unique battle-tested experience allows us to move at blazing speeds.

Restore Hyper Wellness

Senior Data Engineer

I help other organizations start their Data Science projects and help them innovate with Data Science and Machine Learning in areas of their business where there is opportunity to do so.
Areas where I have provided services for other companies and where I can help your business:
•	Probabilistic Programming and Bayesian Inference using tools such as Stan, INLA, and Turing.jl
•	Setting up and scaling out Chatbots and NLU-based platforms.
•	Giving instruction on Programming and Data Science to your team/workforce.
•	Setting up Infrastructure with Terraform.
•	Bringing in existing Infrastructure into Terraform with Terraformer.
•	Deployments of Docker and Docker Swarm.
•	Natural Language Processing Tasks to be run at scale using tools such as Spacy, NLTK, and Dask.
•	Setting up Databases and ETL pipelines and integrating them with Airflow/Prefect.
•	Integrating multiple sources of information into consolidated Databases with ELT.
•	Setting up Dashboards with Tableau and/or Shiny Dashboards.
•	Deploying Reports and creation of report generation processes.
•	Programming tasks with Python, R, or Julia
•	Tasks related to BCI Hardware and EEG software with Python and MNE
•	Scaling out your Data Science pipeline with Python friendly tools such as Dask, Prefect, and. Coiled Clusters.
•	Modifying Open-Source software to better suit your company needs and goals with regards to Data Science and Machine Learning.
•	Implementing Machine Learning pipelines at scale with an MLOps approach towards model development, deployment, maintenance, and setting up of infrastructure.
•	Creation and implementation of long-term MLOps strategies for startups.

Consulting Data Scientist

Freelance/Contract

•	Working on Open-Source projects dealing with Bayesian Inference & Statistics, Probabilistic Modeling & Machine Learning, and Artificial Intelligence.
•	Contributing to Probabilistic Modeling Language Stan by developing and maintaining StanJulia and its related packages.
•	Working on Open-Source BCI applications using tools such as Python, MNE, Sci-kit Learn, Keras, Tensorflow, and PyTorch.
•	Contributing to the Julia package ecosystem via tools for Bayesian Modeling, Inference, and Analysis.

Open Source Developer

Bayesian Data Analysis Meetup

-Organizing events in New York City and remote webinars around Bayesian Data Analysis
-We cover topics ranging to different Probabilistic Programming Languages, software packages dealing with Bayesian Inference and Statistics.
-Our meetup page: https://www.meetup.com/bda-group/

Organizer

NYC Brain-Computer Interface Meetup

•	Advancing knowledge about Brain-Computer Interface (BCI) hardware, techniques, and methodologies within the NYC area.
•	Organizing and management of weekly Open-Source BCI projects.
•	Contributing to Open-Source BCI applications and Analysis of BCI data.
•	Scheduling speakers to talk about BCI topics and their BCI and Neuroscience related research
•	Development of Open-Source AI & Machine Learning methods and applications using tools such as MNE, Keras, Tensorflow, and PyTorch.
•	Collaborating with other meetups in the NYC area to promote knowledge of BCIs and workshops dealing with Neuroscience and Deep Learning & Machine Learning.
•	Mentoring students and other meetup members in Data Science, Deep Learning, Neuroscience, and Programming,
•	Gitlab Page: https://gitlab.com/nyc-bci
•	Slack channel: https://nyc-bci-meetup.slack.com/messages/CC0NVMNM7/details/
•	Meetup page: https://www.meetup.com/NYC-BCI-meetup/

NextSense, Inc

•	Running and maintaining ETL processes on Kubernetes clusters.
•	Standardizing python repositories
•	Setting up of Infrastructure with Terraform
•	Bringing in Existing Infrastructure via Terraformer
•	Setting up ETL pipelines with Airflow, GCP Cloud Composer, and PubSub
•	Integrating multiple sources of information with ELT platforms. 
•	Using Kedro to standardize Data Science projects and implement MLOps standards 
•	Programming tasks with Python and SQL.
•	Working with EEG data at scale using GCP.
•	Scaling out Data Science/Machine Learning pipelines.
•	Implementing long-term MLOps strategies for EEG data using feature stores, experiment tracking standards, and dataset & model versioning.

Virufy

•	Volunteering 10-20 hours a week.
•	Research and identification of state-of-the-art Machine Learning approaches for detecting Covid-19 from coughs.
•	Training, Building, and deployment of AI models into production.
•	Production of clean code and APIs that are of benefit to the development team.
•	Collaborating Product Management and leadership to deliver on expectations.
•	Building data ingestion and transformation infrastructure
•	Processing and feature extraction from a wide variety of data inputs.
•	Identifying transfer learning opportunities and auxiliary training datasets.
•	Formation of results into academic formats such as research papers.

Machine Learning Engineer - MLOps

VillageCare

•	Utilizing various modeling techniques and Python, R, and Stan in analyzing in large and/or complex datasets
•	Overseeing all activities related to data cleansing, data quality and data consolidation using industry standards and processes.
•	Performing explanatory data analysis, generating and testing working hypothesis, preparing and analyzing historical data, and identifying patterns with Python and R.
•	Working closely with cross functional teams to encourage best practices for experimental design and data analysis
•	Working closely with IT technical staff in the identification of external and internal sources and creating efficient and effective data architecture to optimize ongoing analytics and reporting
•	Analyzing provider data and compiling reports for regulatory agencies. 
•	Creating databases and department reports with Python, SQLAlchemy, R, and knitr.
•	Verifying data integrity and reconciling discrepancies in provider data.
•	Assisting with development of department workflows.
•	Developing and implementing automated systems as necessary to ensure efficient operations with Apache Airflow.

Data Scientist

DataKind

•	Working within a team to perform Data Analysis and Data Visualization of third party data.
•	Working with a mission-driven organization that helps support government agencies, nonprofits, and organized social entities with Data Science.
•	Working in a team environment to understand difficult problems.
•	Develop new insights into organizations via Predictive Analytics.

Volunteer

Remedy Partners

• Solving technical data-driven healthcare problems using computer science, advanced mathematical methods, predictive  modeling, statistical methods, and Data Science.
• Establishing scalable, efficient, automated processes for model development, model validation, model implementation, and large scale data analysis using Python.
• Developing metrics and prototypes that can be used to drive business decisions.
• Maintenance of data systems including administrative claims data from Medicare, clinical data from partner providers, and care management data from our staff.
• Regular processing of large scale claims data and episode construction that conforms with established rules, HIPAA, and HITECH guidelines using Python.

Analyst, Episode Analytics

I have a background in Data Science, Healthcare Analytics, Neuroscience Research,  Value-Based Healthcare, Behavioral Healthcare, and Psychology.  I enjoy learning new skills and I'm always open to new and exciting challenges when it comes to working with Data. I also specialize in probabilistic programming.  

taplio

The Battle

Solomon Kahn

Brian Parbhu

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