Rotem Margalit
Data Scientist
Production ML · Multi-Agent Systems · A2A & MCP
Data Scientist at Paycor

Rotem Margalit is a Data Scientist based in Israel, focused on production machine learning, AI agents, multi-agent systems, and applied AI. He builds AI systems that move from prototype to production, using Python, Kubernetes, Terraform, MCP, A2A, graph algorithms, and modern ML workflows.

WHAT I DO
- Production machine learning systems
- AI agent orchestration and multi-agent infrastructure
- MCP and A2A-based agent workflows
- Data science automation and ML pipelines
- Graph algorithms and network analysis
- Workforce analytics and business ML

ABOUT
I build data science and AI systems that reach production. At Paycor, I own the full lifecycle of ML initiatives and multi-agent platforms — framing problems, prototyping models, and deploying solutions inside real business workflows.
I design agent-native infrastructure on Kubernetes and Terraform: an orchestrator agent coordinates specialized sub-agents over the Agent-to-Agent (A2A) protocol, with Model Context Protocol (MCP) servers exposing tools and context to the agent graph.
Before industry, I spent two years as an algorithms researcher at Ben-Gurion University, developing social network analysis methods on large-scale graphs. Teaching deep learning and algorithms to graduate students sharpened how I communicate complex ideas to both technical and non-technical stakeholders.
I hold an M.Sc. in Data Science from BGU's selective Meitar fast-track program, with a thesis in graph-based bibliographic data analysis. My work spans Python, R, and SQL across machine learning, NLP, graph algorithms, agent orchestration, and statistical modeling.

TEACHING & MENTORING
- Graduate-level Deep Learning — feed-forward networks, CNNs, and LSTMs for NLP.
- Foundations of Algorithms and Complexity — reductions, complexity analysis, and algorithm design.
- One-on-one tutoring for Data Structures at Ben-Gurion University.

EXPERIENCE
Data Scientist @ Paycor (Jan 2023 — Present) — Center District, Israel
- Built production multi-agent infrastructure on Kubernetes and Terraform — an orchestrator agent coordinates specialized sub-agents via the Agent-to-Agent (A2A) protocol.
- Integrated Model Context Protocol (MCP) servers as standardized tool and context surfaces for agent workflows.
- Own end-to-end data science and AI initiatives — from problem framing and PoC through production deployment.
- Design and ship AI-driven solutions for complex HR and workforce analytics at scale.

Data Scientist @ getWizer (Jan 2021 — Oct 2022) — Herzliya, Israel
- Built and deployed ML models powering a consumer insights SaaS platform used by global brands.
- Delivered end-to-end pipelines spanning experimentation, modeling, evaluation, and production integration.
- Turned raw survey and behavioral data into actionable product intelligence for marketing teams.

Algorithms Researcher @ Ben-Gurion University of the Negev (Oct 2018 — Oct 2020) — Be'er Sheva, Israel
- Developed social network analysis algorithms on large-scale graph data to identify influential nodes across multiple application domains.
- Implemented high-performance solutions in D, Python, and R.

Teaching Assistant & Tutor @ Ben-Gurion University of the Negev (2017 — Oct 2020) — Be'er Sheva, Israel
- Faculty member for graduate-level Deep Learning — feed-forward networks, CNNs, and LSTMs for NLP.
- Assisted with Foundations of Algorithms and Complexity — reductions, complexity analysis, and algorithm design.
- One-on-one tutoring for Data Structures, mentoring students through core CS fundamentals.

EDUCATION
M.Sc., Data Science — Ben-Gurion University of the Negev (2018 — 2020) [Meitar fast-track program]
Meitar fast-track program for outstanding students, Department of Industrial Engineering. Thesis: graph-based cataloging of bibliographic data and extraction of structured insights at scale.

B.Sc., Industrial Engineering and Management — Ben-Gurion University of the Negev (2015 — 2019)
Information Systems specialization — combining engineering rigor with data-driven decision making.

SKILLS
Languages: Python, R, SQL
ML & AI: Machine Learning, Deep Learning, NLP, Multi-Agent Systems, PyTorch, scikit-learn
Agent Systems: Agent-to-Agent (A2A), Model Context Protocol (MCP), Agent Orchestration, LLM Agents
Infrastructure: Kubernetes, Terraform, Data Automation, A/B Testing
Specializations: Graph Algorithms, Social Network Analysis, Production ML

SELECTED WORK
Multi-Agent Orchestration Platform — Paycor (Jan 2023 — Present)
What it is: Production platform for coordinating LLM agents at scale — Kubernetes-native runtime, Terraform-managed infrastructure, and an orchestrator agent that delegates work to specialized agents over A2A.
- Designed the agent topology: orchestrator dispatches tasks to domain-specific agents via Agent-to-Agent (A2A) messaging.
- Provisioned and managed infrastructure with Terraform; deployed agent services on Kubernetes.
- Exposed external tools and data sources to agents through Model Context Protocol (MCP) server integrations.
Technologies: A2A, MCP, Kubernetes, Terraform, Multi-Agent

Production ML for Workforce Analytics — Paycor (Jan 2023 — Present)
What it is: End-to-end data science initiatives at Paycor — from problem framing and proof of concept through production deployment for HR and workforce analytics.
- Own initiatives across the full ML lifecycle, from PoC to production.
- Design and ship AI-driven solutions for complex HR and workforce analytics at scale.
- Partner with product and engineering teams to integrate models into live business workflows.
Technologies: Production ML, HR Analytics, Python

ML for Consumer Insights — getWizer (Jan 2021 — Oct 2022)
What it is: Built and deployed machine learning models for a consumer insights SaaS platform, turning survey and behavioral data into product intelligence.
- Developed ML models powering a platform used by global brands.
- Delivered end-to-end pipelines spanning experimentation, modeling, evaluation, and production integration.
- Transformed raw survey and behavioral data into actionable intelligence for marketing teams.
Technologies: SaaS, ML Pipelines, Python

Bibliographic Data Cataloging with Graphs — Ben-Gurion University of the Negev (2018 — 2020)
What it is: Master's thesis exploring graph-based methods to catalog heterogeneous bibliographic records and extract structured knowledge from large-scale library datasets.
- Designed graph-based cataloging methods for bibliographic data.
- Extracted structured insights from large bibliographic datasets.
Technologies: Graph Algorithms, Data Science, Python

Large-Scale Social Network Analysis — Ben-Gurion University of the Negev (Oct 2018 — Oct 2020)
What it is: Research project developing social network analysis algorithms to identify key actors in massive networks across diverse application domains.
- Built SNA algorithms for large-scale graph data.
- Implemented solutions in D, Python, and R.
- Benchmarked across diverse real-world graph datasets.
Technologies: SNA, Python, R, D

FAQ
Who is Rotem Margalit?
Rotem Margalit is a Data Scientist focused on production machine learning, AI agents, and applied AI systems.

What does Rotem Margalit work on?
He works on production ML workflows, AI agent orchestration, MCP, A2A, Kubernetes-based infrastructure, graph algorithms, and applied data science systems.

Where is Rotem Margalit based?
Rotem Margalit is based in Israel.

How can I contact Rotem Margalit?
You can contact him via email at rotem@margalit.ai, through LinkedIn, GitHub, or this website.

CONTACT
Email: rotem@margalit.ai
LinkedIn: https://www.linkedin.com/in/rotem-margalit-b56240b1/
GitHub: https://github.com/rotema7
Website: https://www.margalit.ai

Last updated: June 2026