PyData Tel Aviv 2025

Machine Learning Manager with advanced skills in GenAI, Agentic flows, Recommendations, Reinforcement learning algorithms and simulations. In addition, experienced in Operations Research with a demonstrated history of working in the Defense & Space industry, Autonomous vehicles and E-commerce recommenders. Skilled in Conceptual System Design, Machine Learning, Numerical Simulation, Statistical Data Analysis, Discrete Event Simulation, and Python (Langgraph, Pyspark, Pytorch, Scipy, Pandas etc.). Strong research professional with a Master's degree in Applied Mathematics from Technion - Israel Institute of Technology. Thesis focuses on Combinatorial Optimization problems with multi agents and reinforcement learning algorithms. Recenetly Focused on GenAI for the travel industry including free text search, ai trip planner and other travel products utilizing GenAI to under user queries.

Hi! I'm Daniel, a machine learning research engineer from Israel.

I started my career as a programmer, and had the opportunity to take on a range of roles: FS developer, team lead, and course instructor.
I then got into the world of data science / ML in Nutrino - a nutrition startup that was later acquired by Medtronic.

After that I ventured out on my own as a freelance machine learning practitioner; now I work with several startups on ML / vision problems. I also work with an Israeli non-profit, helping to create and improve tech-ed programs for youth.

Bachelor's degree in computer science from the Open University, Master's degree in machine learning & data science from Reichman University.

Partial list of things I'm excited about:

• Algorithms and optimizations
• Translating experts’ domain knowledge and intuition into concrete methods and metrics
• Designing ad-hoc models that make the most of little data (mostly because that involves designing custom metrics and coming up with creative ways of optimizing them)
• Finding patterns in behavior
• Creating interactive visualizations to explore complex data and interactions

Also, I have a blog!

Dan Ofer received the B.Sc. degree in psychobiology, in 2013, and the dual M.Sc. degree in bioinformatics and neurobiology from The Hebrew University. He is currently a PhD Candidate with Professor's Dafna Shahaf and Michal Linial, and an AI Researcher in industry since 2015. Previously, at SparkBeyond/McKinsey he developed AI solutions in multiple industries, including insurance, finance, healthcare, and novel biomarker discovery with CRI. His research interests include Biological Foundation models, explainable AI, automated feature engineering on tabular data, Protein LLMs, and AI in healthcare.
Passionate Bookworm, geek and Photographer

Gal Benor is a Machine Learning Scientist at PayPal. In her day-to-day projects she focuses on developing transparent fraud detection models that safeguard users. She is passionate about eXplainable AI (XAI) and works to make machine learning more interpretable and tailored to specific needs. Gal earned a BSc in Computer Science from Ben-Gurion University and an MSc in Applied Mathematics and Systems Biology from the Weizmann Institute of Science, where she focused her research on breast cancer—an area where transparency is critical, and black-box models are not an option.

Data analyst, researcher and economist.
Sci-Fi geek, beer lover, and have a personal intrest in unique names.

Linoy Cohen is a Senior Data Scientist at Intuit in the NLP team. As part of her role, she leads the evaluation track and is responsible for creating automatic evaluations for LLMs and Agents that provide an objective method to measure their capabilities based on specific custom criteria and needs.

Lior Kupfer, creator of Tabbers. With a background in AI, Applied DS, Analytics, and Product Development and Management, I’m passionate about building smarter, user-friendly systems that create real impact.

I am a biologist interested in the interface of AI, big data and life science. My current work comprises systems to automatize data-driven science with AI and reinforcement learning systems to control experimental workflows in microbiology and evolution.

Maria is a CTO and co-founder of Rokka, bringing over six years of data science expertise from Intel, EY, and Playtika.
A natural entrepreneur, she previously founded and scaled a successful chain of beer bars to ten locations in just one year.
As a CTO with extensive experience in both corporate and freelance environments, ranking 74th out of 57,000 clients on one of the biggest Freelance platform, she can share insights from successfully managing over 150 small projects as well as leading a product development team.
Today, she combines her technical leadership with a passion for education, running a practical training school for aspiring QA specialists and Data Analysts.
Her proven track record in both technology and business leadership, along with her hands-on teaching approach using real-world cases, makes her a compelling speaker and mentor in the tech community.

Miki has been shipping bugs to production for over 28 years.
He has a passion for teaching, mentoring, and talking about tech for way too long.
Miki contributes to open source, either his own projects, or external ones - including the Go and Python projects.

Miki wrote several technical books, he's a LinkedIn Learning author and an organiser of Go Israel Meetup, GopherCon Israel, and PyData Tel Aviv Conference.

When not geeking out, Miki likes to climb, hike all over the world, read books and annoy his family.

Moran is a Senior Machine Learning Manager at booking.com, researching and developing GenAI, NLP and CV models for the tourism domain.
Moran is a Ph.D candidate in information systems engineering at Ben Gurion University, researching NLP aspects in temporal graphs.
Previously worked as a Data Science Team Leader at Diagnostic Robotics, building ML solutions for the medical domain and NLP algorithms to extract clinical entities from medical visit summaries.

Data Science and Engineering Team Lead @ LSports, Lecturer at the AI Developers and Data Analytics program @ Hebrew University and WiDS Community manager.

Noa Henig holds a B.Sc. in Computer Science from the Hebrew University and a Ph.D. in Medical Sciences from the Technion. Noa is a Data Scientist specializing in Genomics, with extensive experience in biological data analysis. Her professional experience spans startups, corporations, and medical institutions in both the US and Israel. Outside of work, Noa enjoys jogging, photography, and listening to podcasts.

Noa Radin is a Data Scientist at HoneyBook, where she works on improving user onboarding and product experience. Prior to that, she led a data science team at ThetaRay, designing anomaly detection solutions for global banks and fintechs. Noa holds an M.Sc. in Data Science and Engineering from Ben-Gurion University. In her free time, Noa enjoys hiking and relaxing at the beach.

My name is Omer, and I am a PhD candidate at the Technion - Israel Institute of Technology. My primary research field is algorithmic game theory and its applications in data science. In particular, I am interested in information design, mechanism design, and learning dynamics in the context of recommendation systems and search engines. My expertise includes mathematical economic modeling, applied ML, and integrating LLMs and GenAI into economic and strategic decision-making.

I also hold an MSc in data science and a BSc in data science and engineering, both from the Technion. During my bachelor's studies, I completed two internships at Google, working on various software engineering projects.

I am a data scientist with a strong background in software engineering and system development, currently helping protect Web3 as a DS in Blockaid.

I'm passionate for solving real-world problems through machine learning, big data technologies, and algorithm development, and have a proven track record of taking data-oriented projects from ideation to production in various fields.

Ortal Ashkenazi is a Data Scientist at Wix, specializing in natural language processing and applied machine learning. She enjoys turning messy, human language into structured, useful insights — bridging the gap between raw data and real-world decisions. With an MSc from the Technion, she combines academic depth with hands-on product thinking to build AI tools that people actually use.

Reuven is a full-time Python trainer, teaching at companies around the
world and also via his online platform at LernerPython.com. Reuven
publishes two weekly newsletters, Better Developers (about Python) and
Bamboo Weekly (Pandas puzzles based on current events), and has an
active YouTube channel about Python and Pandas. In the last few years,
Reuven published two books of practice exercises with Manning, Python
Workout and Pandas Workout. Reuven has a degree in computer science from
MIT and a PhD in learning sciences from Northwestern University.

Over a decade of industry experience in the Intersection of DS/ML and Cyber; in the last year I'm working on LLM Apps @ Blinkops .

Shirli is a senior AI scientist at Intuit, where she brings cutting-edge innovation to life through generative models and agentic AI. Her areas of expertise span reinforcement learning, LLM training and evaluation, NLP, classical machine learning, and the design of intelligent agents.

Shirli holds a Ph.D. and M.Sc. in Electrical and Computer Engineering from the Technion, specializing in Reinforcement Learning, and a B.Sc. in Biomedical Engineering from Ben Gurion University.

Shuki Cohen is an AI Evangelist at AI21 Labs, on a mission to make Artificial Intelligence more accessible, understandable, and impactful for anyone curious about its potential. AI21 Labs is pioneering the development of enterprise AI systems and foundation models, turning cutting-edge research into enterprise-grade AI solutions built for the agentic future.

With an M.Sc. in Industrial Engineering, specializing in Data Science from Tel Aviv University, Shuki brings a strong technical foundation and a passion for sharing the power of AI through clear, engaging and crisp takeaways.

Sigal Shaked is a founder, technologist, and researcher with over 20 years of experience at the intersection of data, machine learning, and Generative AI. She holds a PhD in Software and Information Systems Engineering and was among the early academic contributors to the emerging field of GenAI. At Datomize, she led the development of a GenAI-powered synthetic data platform, and today, at Datawizz, she focuses on building domain-specific small language models (SLMs) that prioritize performance, privacy, and real-world utility.

MSc in Data Science, Algorithm Engineer at Mobileye

Tal Mizrachi (a.k.a. Analysis Paralysis) is a data scientist, educator, and mentor on a mission to make data science, analytical thinking, and programming more approachable—and more fun than it already is. He loves helping people connect the dots, ask better questions, and build cool stuff with data. When he’s not wrangling datasets or teching Python in TAU, Tal is usually hanging out with his wife Adi, their two daughters, and a very large black dog.

Prof' Teddy Lazebnik is a applied mathematics and computer science researcher with extensive experience leading RnD teams in both the life sciences and financial domains. Over the past decade and a half, Teddy has honed his software development skills, including nine years of experience managing development teams of up to fourteen professionals. Teddy has a proven track record in system architecture, developing production-ready algorithms, and collaborating with clients. His expertise includes bio-physical simulations, big data analysis, and data analysis for information systems. His research is focused on applying advanced mathematics and computer science to the life sciences and socio-economic domains, covering areas such as AI-driven personalized treatment protocols, drug discovery, eXplainable AI, socio-economic systems modeling and simulation, and optimal policy detection from financial data.

M.Sc. CS & Math student at Weizmann Institute of Science; ivrit.ai co-founder (non-profit)

AI & Tech Consultant, ivrit.ai

ML Engineering Team Lead at Voyantis with extensive backend engineering experience across diverse tech companies.
I oversee ML technical initiatives, having transformed our ML cycle with a scalable SQL-based platform and built an advanced inference service for large-scale predictions. When not reimagining machine learning systems, I share insights through my publications on Towards Data Science.
Passionate about driving technical innovation in the data world.

Ilana Makover enjoys finding bugs and solving them. She is a Machine Learning Engineer at Bluevine.