Posts By

Zach Blumenfeld

Data Science Product Specialist, Neo4j

Zach Blumenfeld is a graph enthusiast who helps data scientists, engineers, and business leaders understand and implement Graph Analytics to solve challenging business problems.

He has firsthand experience with a wide range of modern day analytical challenges, including criminal fraud detection, identity resolution, and recommendation systems. Serving in both data science and software developer capacities, Zach has applied graph computing for law enforcement and government entities in support of missions that counter drug trafficking, human smuggling, money laundering, and child exploitation. He has led the development and deployment of full stack graph systems designed to facilitate broad search and analytical query requirements.

Zach is excited to join Neo4j as Data Science Product Specialist, where he will help empower the field with Neo4j’s industry leading Graph Data Science (GDS) capabilities.

GraphRAG Python package.

GraphRAG Python Package: Accelerating GenAI With Knowledge Graphs

11 min read
What is retrieval-augmented generation RAG)?

What Is Retrieval-Augmented Generation (RAG)?

5 min read

The Definitive Guide to Building a Predictive Model in Python

11 min read

Predictive Modeling Techniques: Types, Benefits & Algorithms

12 min read

Demystifying Graph Neural Networks

2 min read

Graph Data Science for Supply Chains – Part 3: Pathfinding, Optimization, and What-If Scenarios

15 min read

Introducing the New Neo4j Data Warehouse Connector

4 min read

Graph Data Science for Supply Chains – Part 2: Creating Informative Metrics and Analyzing Performance in Python

10 min read

Graph Data Science for Supply Chains – Part 1: Getting Started with Neo4j GDS and Bloom

13 min read

Exploring Fraud Detection With Neo4j & Graph Data Science  –  Part 4

8 min read

Exploring Fraud Detection With Neo4j & Graph Data Science  –  Part 3

5 min read

Exploring Fraud Detection With Neo4j & Graph Data Science  – Part 2

6 min read