Full Stack Data Scientist

Sorry, this job was removed at 06:22 p.m. (CST) on Thursday, Jul 17, 2025
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Hiring Remotely in Tel Aviv, ISR
Remote or Hybrid
Productivity • Sales • Software
Shaping the way the world works with the best AI work platform.
The Role
Description

We are monday.com, a global software company transforming how businesses run. Our product suite can adapt to the needs of diverse industries and use cases within one powerful platform, empowering ~245,000 customers worldwide to reimagine how work gets done, drive greater efficiency, and scale like never before.

With over 2,500 employees across the globe, we grow by prioritizing transparency and knowledge sharing. We care about the impact you make, not the hours you clock, so we encourage initiative, ownership, and fresh thinking. We back our people with flexible work, wellness and mental health support, and a work environment built on collaboration.

As a Full Stack Data Scientist at monday.com, you will be at the forefront of integrating cutting-edge AI capabilities across our platform. You will play a pivotal role in developing and deploying AI-driven features that enhance our CRM, Open Platform, and AI R&D initiatives. Your work will directly impact how businesses manage relationships, build software, and leverage AI to create new user experiences.

Why Join Us?

Be part of one of the fastest-growing SAAS platform companies, with AI at the core of our future.

Work on impactful AI-driven projects that redefine how businesses operate and build software.

Join a highly collaborative, innovation-driven team that values creativity and data-driven decisions.

Enjoy a dynamic work environment with opportunities for growth, learning, and leadership.

If you’re excited about building the future of AI-powered platforms and transforming how businesses run, we’d love to hear from you!

#LI-DNI


About The Role
  • Utilize generative AI technology to create innovative features within monday.com's ecosystem.
  • Initiate, plan, design, and execute AI flows from research to production.
  • Collaborate with full-stack developers, product managers, data analysts, product designers, and other stakeholders to build production-ready capabilities for over 2 million users.

Requirements
  • 4+ years of experience as a Data Scientist in non-academic settings, with a focus on Large Language Models, NLP, or other deep learning fields.
  • Proven track record of conceiving, designing, and shipping successful agentic-driven projects to production.
  • Hands-on proficiency with modern generative AI models, prompt engineering, multi-agents, and RAG architectures.
  • Solid understanding of transformers and evaluation methodologies of LLMs using frameworks like Hugging Face, LangChain, and LlamaIndex.
  • Proficiency in Python is a must; knowledge of Typescript is an advantage.
  • Team player with strong communication skills.
  • B.Sc. and ideally an advanced degree in a technical field such as Computer Science, Mathematics, Statistics, or equivalent experience.

Social Title

Full Stack Data Scientist


Social Description
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What the Team is Saying

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The Company
HQ: New York, NY
3,049 Employees
Year Founded: 2012

What We Do

At monday.com, we help teams get more work done. We are the best AI work platform that empowers teams to automate, build, and scale their impact end-to-end with tools that actually execute the work for you. With over $1B in ARR, 250,000+ customers, and a global team, we’re serious about building a product people love to use and giving our employees the same ownership and flexibility to shape the way the world works.

Why Work With Us

At monday.com we believe in transparency, accountability, and impact. Together, those values have lent themselves to create a strong culture of professional and creative autonomy where every team member is encouraged to share ideas and help bring them to life!

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monday.com Offices

Hybrid Workspace

Employees engage in a combination of remote and on-site work.

monday.com embraces a flexible work environment with our hybrid model!

Typical time on-site: 3 days a week
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