GLENN SOLOMON

Sr. Engineer / Sr. Data Scientist
215-450-2084 | gsolomon11@gmail.com
InterwebAnalytics.com | linkedin.com/in/gsolomon1039
Skills
AI / ML / Statistics
PyTorch, TensorFlow, Keras, HF Transformers, | LSTMs, Autoencoders, GNNs, CNNs | Deep Familiarity with LLMs | Anomaly Detection, Binary Classification, Time Series Analysis, Clustering, Probability, VAR, Portfolio Optimization, Earth Mover's Distance, Granger Causality
Databases + Storage
Clickhouse, PostgreSQL, MySQL, SQLite, MongoDB, Redis | Prometheus, Elasticsearch, InfluxDB, Lucene | Production DB Migrations | Blockchain | CSV, JSON, Parquet, Pickle, HDF5, Avro
ETL / Data Processing
Python, Bash, Rust, R, PySpark, Scala, SAS | Kubernetes, Kafka, AWS, Databricks, Kibana, Splunk | Pandas, NumPy, Polars, Airflow, MLFlow, TSfresh, Fastdtw | Stream Processing, Performance Computing, Web Scraping
UI / Visualization
JS, HTML, CSS, D3.js, Three.js, Leaflet.js | React, NextJS, PHP | Tableau, Superset, Grafana | Nginx, Apache HTTP, Node.js, WebSockets, Proxy + Auth
Server + GPU Cluster
Linux system configuration, various package managers, data migrations, GPU driver, library, and frameworks
Other
Mac, Windows, Linux | PowerPoint, Excel, Outlook, JIRA, Slack, Teams
Summary
Experienced Data Scientist, Engineer, and initiative leader with 9+ years of progressively increasing responsibility, serving as go-to resource for handling novel, large-scale data projects and forging cross-domain relationships.
Extensive experience building full-stack data applications with expertise in data engineering, artificial intelligence, machine learning, and visualization, specializing in massive-scale, real-time data platforms with strong understanding of how probability and classical statistics complement AI/ML.
Rare combination of knowing which statistical tool, algorithm, or neural network architecture is suitable for a given task.
Education
MS Business Analytics
Drexel University, LeBow College of Business
Philadelphia, PA | 2016 | GPA 3.80
Concentration in Statistics
Alumni Merit Scholarship Recipient
Michelin Connected Mobility Challenge, Winner for "Innovative Solution in the Connected Mobility Domain."
Philadelphia 76ers Internship, Built innovative metrics display for pro basketball analytics department.
BA Economics
Muhlenberg College
Allentown, PA | May 2010
Other
Have mentored 8 students from Muhlenberg College. This includes virtual learning and Q/A sessions along with allowing them to shadow me in person at work.
Programmed Raspberry Pi sensors for custom applications.
Work Experience
Comcast, Philadelphia, PA
9/2016 – Present
Sr. Software Engineer
Program Lead / Technical Owner — Sky UK Data Integration (2025–Present)
  • Serve as single technical point of contact between Comcast and Sky UK for data integration affecting hundreds of downstream customers and dashboards.
  • Own end-to-end architecture and execution of migrating billions of daily streaming events from Sky UK onto Comcast infrastructure, including schema design, storage tradeoffs, and sampling strategies.
  • Drive cross-organization prioritization and rollout coordination for new Sky datacenter deployments.
Massive Scale Data Ingestion and Database Platform Monitoring (2023 to 2025)
  • Led critical monitoring initiative for Comcast's largest in-house database platform, spanning geo-distributed Kafka–Zookeeper–Kubernetes stacks and hundreds of ClickHouse servers ingesting ~1T events/day from 10,000s of heterogeneous log forwarders.
  • Created end-to-end real-time ML anomaly detection and root cause analysis application using ensemble of statistical thresholds, Mahalanobis/DTW distances, and AutoEncoders from ideation through production deployment.
  • Established ongoing collaboration with platform engineers to understand operational pain points and implement optimal real-time alerting workflows.
  • Reduced mean time to detect and remediate issues, saving hundreds of engineer hours through automated anomaly detection and intelligent alerting.
Predictive and Proactive Remediation of Poor Customer Experience (2021 to 2023)
  • Created live prediction system for detecting and proactively treating error-prone customer streaming sessions across 10,000s of concurrent sessions, serving predictions to production CDN infrastructure.
  • Spearheaded GPU training cluster setup, evaluated diverse neural network architectures and built feature store of 100M+ training samples using advanced feature selection and domain expert collaboration.
  • Developed intuitive user interface displaying real-time predictions and accuracy metrics, using it as teaching tool to present model interpretability to hundreds of engineers.
  • Pioneered Comcast's first AI/ML deployment to CDN edge infrastructure, informing future intelligent bitrate and proactive session rerouting capabilities.
Integration of Disparate Data Sources for Automated Root Cause Analysis and Alerting (2019 to 2021)
  • Conceived and created Belvedere, a novel root-cause system monitoring and combining billions of real-time events from Last-Mile Infrastructure, Datacenter, and Customer Device sources to enable cross-silo analysis.
  • Built custom user interface displaying poor customer experiences geographically in real time with continuously updated metrics and user-configurable alerting for specific scenarios.
  • Collaborated extensively with domain experts across company verticals to define application logic, validate data quality, and ensure operational relevance.
  • Enabled Video teams to root-cause errors en-masse and Infrastructure teams to monitor rollouts, saving thousands of analyst hours and informing truck roll decisions; impact led to dedicated team formation.
Management of Massive ETL Pipeline Capacity Planning of $100M of Cloud Server Infrastructure (2016 to 2019)
  • Managed end-to-end ETL pipeline ingesting, transforming, and reporting on 120,000 ~100MB compressed files per day (12TB total), supporting cloud DVR storage infrastructure decision-making.
  • Optimized high-velocity data pipeline through custom C parsers, database partitioning, bulk insertion strategies, and disk formatting optimizations to handle scale requirements.
  • Maintained and ran stepwise regression models for capacity forecasting, delivering regular reports to senior leadership.
  • Directly influenced capacity planning and tens of millions of dollars in cloud DVR storage infrastructure investments with IBM through data-driven analysis.
Freencer Labs, Philadelphia, PA
4/2016 – Present
Front-End Developer
  • Developed a UI and interactive visualizations enabling researchers and patients to identify cancerous gene segments.
LexisNexis, King of Prussia, PA
2012-2015
Data Analyst
  • Gathered, cleaned, sourced, standardized and ran statistical tests on millions of claims, healthcare practitioner, and Medicare records daily while managing $1+Mil location intelligence/geocoding databases contract.
  • Initiated programs with two medical boards and created team wiki page documenting best practices.
Recyclebank, Philadelphia, PA
2011-2012
Assistant Data Analyst
  • Maintained and integrated multiple databases, wrote SQL queries to automate data extraction, and managed daily inflow of large data files including aggregation, analysis, scrubbing and cleaning.
  • Conducted daily reporting requests from Data Management and Analytics department and created procedural manual detailing decision-making processes.
ECRI, Plymouth Meeting, PA
2007 & 2010
Internships - Research Assistant & Web Content Specialist
  • Rated and evaluated healthcare IT businesses using robust qualification criteria and identified potential partnering opportunities for federal government contracts.