Description
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.
We are seeking an experienced, creative, and impact-driven Senior Data Scientist to join our BigBrain team!
The Data Science group at BigBrain partners closely with teams across monday.com to drive and define key company KPIs and help achieve our most ambitious goals. As a Data Scientist, you’ll lead the ML and AI efforts behind your projects, empowering our marketing, sales, product, and customer experience teams with smart, practical, data-driven solutions. You’ll join a multidisciplinary group that includes developers, data engineers, analysts, and product managers, all working together to create a meaningful impact for our users.
You will work directly with rich, real-world datasets to tackle a diverse mix of challenges with ML and AI initiatives help marketing measurement and optimization, building agents and intelligent assistants, predicting customer intents and lifetime value, delivering personalized recommendations to improve product discovery, enhancing the CX experience with predictive insights and automated replies, and much more.
See some more on BigBrain here:
**https://www.youtube.com/watch?v=x-m0ag0cty0**
**https://engineering.monday.com/meet-the-geniuses-behind-our-bi-tool-bigbrain/**
About The Role
The BigBrain group is looking for a Senior / Tech Lead Data Scientist to own and drive our marketing and growth data science domain. This is a leading position with a mandate to play offense: set the technical direction, push the organization toward higher-leverage problems, and shape how marketing, growth, and operations use data science at monday.com.
You'll be the data science authority for one of our most analytically demanding areas, partnering with marketing and growth leadership, analyst teams, engineers, and product to translate business challenges into measurable ML and statistical impact.
You will:
- Own a portfolio of production ML models that drive marketing and growth decisions across the funnel, including early ARR prediction for new entities entering the system, lead scoring, and other models powering acquisition, monetization, and retention.
- Lead our experimentation infrastructure, including geo-experiments and AB testing. You'll set the bar for how complex experiments are designed, how causal impact is measured, and how the organization makes decisions under uncertainty.
- Guide our marketing and growth analyst teams. Elevate their work, set technical direction, identify where data science can solve problems analysts can't, and grow the analytical capability of the organization around you.
- Train and enable business and operational teams on the models and frameworks you build. Adoption is part of the job, and a great model nobody uses is a failure.
- Drive marketing and growth into the agentic era. Identify where LLM-based and agentic workflows can replace, augment, or accelerate existing processes, prototype them, and bring them to production.
- Play offense on the roadmap. Don't wait for problems to land on your desk. Proactively surface the highest-leverage opportunities, challenge assumptions, and set ambitious targets for what data science should deliver.
- Own problems end-to-end, from ideation through production, monitoring, and iteration, balancing quick wins against long-horizon bets.
Requirements
- 6+ years of hands-on Data Science and Machine Learning experience, with a track record of production models that drove measurable business impact, ideally in a hyper-growth environment.
- MSc or higher in a quantitative field such as Data Science, Computer Science, Statistics, Physics, Mathematics, Industrial Engineering, or similar
- Demonstrated technical leadership: setting direction on ambiguous problems, mentoring strong ICs, and being the person others turn to for the hard calls.
- Strong foundations in machine learning and statistics, with proven ability to ship production-grade models, not just notebooks.
- Proficient in Python and SQL, comfortable across the modern ML and data stack.
- Proactive operator. You don't wait to be told what to work on. You identify the highest-impact problem in the room and go after it.
- Excellent communicator across audiences, able to explain a model to an operations team, defend a design choice to engineers, and frame business impact for executives.
- Strong business orientation and instinct for prioritizing impact over novelty.
- Genuine drive to experiment with new techniques, including generative AI and agentic systems.
- Demonstrated technical leadership: setting direction on ambiguous problems, mentoring strong ICs, and being the person others turn to for the hard calls.
- Experience with causal inference, geo experiments, incrementality testing, or marketing mix modeling - plus
- Experience applying data science to marketing, growth, or monetization use cases - plus
- Hands-on work with LLMs or agentic frameworks in production - plus
#LI-DNI
Social Title
Senior Data Scientist (BigBrain)
Social Description
The Data Science group at BigBrain partners closely with teams across monday.com to drive key company KPIs and help achieve our most ambitious goals. As a Data Scientist, you’ll lead the ML and AI efforts behind your projects, empowering our marketing, sales, product, and customer experience teams with smart, data-driven solutions. You’ll join a multidisciplinary group that includes developers, data engineers, analysts, and product managers—all working together to create a meaningful impact for our users.
You will be exposed to real-world challenges such as: marketing budget optimization, building co-pilots and intelligent assistants for internal teams, predicting customer intents and lifetime value, delivering personalized recommendations to improve product discovery, enhancing the CX experience with predictive insights and automated replies, and much more.