דרושים » תוכנה » Data Scientist

We are looking for a passionate Senior Data Scientist to join our all-star team. This is an amazing opportunity to join a multi-disciplinary A-team while working in a fast-paced, results, marketing and data-oriented environment. If you are experienced but still hungry to learn and impact - wed love to have you on our team!



What Youll Do

Devise, initiate, manage, and execute cutting-edge exploration and exploitation projects.
Apply your knowledge of Data Science, Machine Learning, and AI-driven algorithms to create scalable data solutions.
Analyze extremely large (petabytes) and diverse datasets to solve complex problems, and develop automated, intelligent systems to address them.
Design, build, and deploy AI/ML models (including predictive models, recommendation systems, and generative AI solutions) to drive business impact.
Leverage modern AI tools and frameworks to accelerate research and production workflows.
Proactively seek growth opportunities aligned with core KPIs.
Enable real-time and near real-time data insights - instant data gratification guaranteed.

We are seeking an agile, hands-on R&D Lead who excels at rapid learning and making smart, pragmatic decisions to drive our core data engineering squad in Tel Aviv. We care less about years spent in formal management or having a decades-long resume, and much more about your ability to take extreme ownership, learn new paradigms on the fly, and keep the team moving forward.


In this role, you will help architect, write, and deploy the Python-based infrastructure that processes millions of records daily and serves them at sub-second latency to autonomous AI systems. You will guide the design of high-scale data pipelines, integrate semantic search paradigms, and build out our agentic connectivity layer. If you are a proactive decision-maker who thrives on optimizing complex systems and wants to build the infrastructure that LLMs rely on to understand the real world, this is your next role.


Key responsibilities
Execution & Decisive Leadership: Lead the technical delivery by setting the pace and making pragmatic architectural choices that keep the team moving forward. You prioritize shipping and iterating over analysis paralysis.
Hands-On Development (Python): Roll up your sleeves and remain technical. Write clean, concurrent, and scalable Python code to handle data ingestion, transformation, and serving pipelines.
Continuous Learning & Tech Agility: Work across a polyglot environment. You dont need to know every tool on day one, but you must be eager to rapidly evaluate, learn, and adopt the optimal databases, message brokers, and execution frameworks to manage technical debt.
Agentic Infrastructure & MCP: Deploy systems that allow autonomous agents to seamlessly query our datasets. You will help build and scale our Model Context Protocol (MCP) servers, translating LLM intents into highly optimized database queries.
High-Scale Data Pipelines: Oversee an end-to-end data architecture capable of supporting continuous ingestion, error cleansing, and near-real-time refreshing of a 1B+ record database while enforcing GDPR and CCPA compliance.
Search & Retrieval Integration: Design and optimize advanced search capabilities, leveraging vector databases, embeddings, and hybrid search techniques to ensure absolute precision when AI models query our data.

We're looking for a Data Scientist (extended maternity leave cover) to push our ML capabilities further into the platform. Models are already running in production - your job is to make them sharper, keep them honest as the data shifts, and find the next opportunities worth building. This isn't a research-only role. It's an ownership role, end to end.

In this role, you will:
New ML opportunities get identified and proven out before engineering time is spent on them, because you research, prototype, and validate the model first.
Complex ideas land clearly across teams, because you can explain a model's logic and tradeoffs to engineers, product, and stakeholders without losing the substance.
Models keep working after they ship, because you own the full lifecycle: development, production deployment, drift monitoring, and retraining as the data changes.

We are looking for an experienced, independent team player who has great data & computer science skills, a passion for data, and excellent analytical and algorithmic skills.

This role is diverse, encompassing AI/ML, data analysis, and backend engineering.

You will play a crucial role within a mission-critical team responsible for managing the heart and brain of Sunbits primary products. This involves working on core systems, such as POS underwriting models, models for merchant operations, Fraud investigator AI agents and more.

You will participate in cutting-edge risk management systems that safeguard the loan product's financial operation, as well as operational systems, with a direct impact on its financial success.

Our AI/ML team is part of the R&D group, so you will work closely with engineers and product managers as well.

Key Responsibilities
Research and develop statistical behaviors, study domain-specific data.
Develop state-of-the-art machine learning models end to end, including development, deployment, and continuous improvement. Both in-weight learning and in-context learning, for risk / fraud / operations related projects. This includes integrating models into production services and ensuring compliance with regulatory processes (e.g. providing evidence for production model audits).
Operate backend infrastructure for training and deploying ML models, ensuring optimal performance and reliability.
Develop and maintain Python code for translating ML model outputs into financial decisions.
Analyze 15+ different data sources in order to train models and agents to catch fraudulent patterns.
Conduct analytical research on our models impact on the portfolio.
Strategize and implement changes to enhance portfolio performance.

we are disrupting performance marketing, delivering millions of new customers to brands every month. We're hiring a hands-on Senior Applied Data Scientist to help build and scale production-grade recommendation systems that drive our core marketplace outcomes.
This is not a research-only role. We're looking for someone who can take models from idea to production - running experiments, measuring business impact, and continuously improving the systems behind how our company matches people with the right brands. You'll own the full lifecycle: exploratory analysis, data prep, modeling, testing, deployment, and post-launch measurement.
The ideal candidate has worked in a real production environment, brings strong deep learning experience, and understands recommendation systems in practice - not just in theory. Success here means shipping models that move our company's core KPIs, connecting technical work to measurable business impact, and helping the team scale with strong engineering discipline.
This role is ideally based in Israel, but strong candidates in the U.S. will also be considered.
What You'll Do
Own the full funnel of applied machine learning work, from idea through production
Build, improve, and deploy recommendation models that support our company's core business goals
Tackle deep learning problems in a production setting - not just offline experimentation
Conduct exploratory data analysis, preprocessing, feature development, and modeling
Run experiments and evaluate success against business KPIs, not just model metrics
Partner with engineering and infrastructure teammates to productionize models and scale systems
Improve recommendation quality, personalization, and the business performance tied to those systems.

As a Fraud Data Scientist, you will be at the front lines of protecting our ecosystem from sophisticated financial fraud and abuse. You will join a high-impact team operating in a data-rich, high-frequency environment where seconds matter.
In this role, you will take ownership of the end-to-end machine learning lifecycle-from uncovering complex fraud patterns to deploying highly scalable, real-time models into production. You will collaborate closely with Engineering, Product, and Risk Operations to build robust defenses that balance strict security with a seamless user experience.
What You Will Be Doing
Model Development & Deployment: Design, train, and deploy advanced machine learning models (e.g., gradient boosting, anomaly detection, graph networks) to detect and mitigate fraud in real-time.
Production Ownership: Take full ownership of putting models into production systems, ensuring low-latency execution and high reliability.
Agentic Workflows: Research, build, and implement Agentic flows and LLM-driven orchestration to automate multi-step fraud decisioning, logic routing, and investigation paths.
Adversarial Analysis: Conduct deep-dive exploratory analysis on massive datasets to identify emerging fraud vectors, loops, and coordinated attacks.
Feature Engineering: Build and optimize real-time streaming and batch features to improve model signal and precision.
Experimentation & Monitoring: Design rigorous shadow-testing and A/B testing frameworks for new models. Set up continuous monitoring pipelines to catch data drift and performance degradation early.

The ideal candidate is passionate about data and AI, comfortable navigating complex systems, and excited by the opportunity to operationalize AI within a modern enterprise environment. We value curiosity as much as experience: we are looking for someone eager to show what they know, and equally eager to keep learning in a field that moves fast.

Responsibilities
Explore, analyze, and model large volumes of structured and unstructured data in Python, from exploratory analysis and feature engineering through to model validation and communication of results.
Design, train, evaluate, and deploy machine learning models, and monitor their performance, accuracy, and drift in production.
Build and orchestrate Agentic AI solutions - LLM-based agents, RAG pipelines, prompt design, and evaluation frameworks - to automate data quality checks, investigation, and reporting workflows.
Integrate models and agents with internal systems and data sources using MCP servers and clients, and workflow automation platforms such as n8n.
Write efficient and maintainable SQL queries to support analysis, reporting, and data exploration needs.
Collaborate with data engineers to productionise models and agents: reliable data flows, logging, alerting, and performance tuning.
Participate in the development of internal tools and dashboards that make data and AI capabilities accessible across the organization.
Share findings with the team and help evaluate emerging AI tooling as the ecosystem evolves.

We are looking for a passionate Data Scientist Team Lead to join our all-star team. This is an amazing opportunity to join a multi-disciplinary A-team while working in a fast-paced, results, marketing and data-oriented environment.

You will become the focal point of our data team and streamline processes, and will be responsible over company revenue streams.



What Youll Do

Mentor a team of extremely talented and success-hungry data scientists.
Initiate and manage cutting-edge projects from inception to delivery, including developing structured and automated solutions.
Lead the data strategy: be responsible for planning, prioritizing, and building the right data solutions to support business needs.
Apply your scientific knowledge and creativity to analyze large volumes of diverse data and develop algorithmic solutions and models to solve complex problems.
Identify and propose data science and algorithmic solutions for various product initiatives.
Use your excellent communication skills, both written and verbal, to explain technical concepts and analysis implications to senior leaders, and influence cross-functional teams to improve performance.
Partner with other departments (i.e. Management, R&D, Product) to support decision making.

We are seeking an experienced Data Science Team Lead to lead our data science and data engineering efforts and oversee a team of skilled data engineers. This role combines hands-on technical leadership and team management, with responsibilities that include building and scaling data infrastructure to power real-time pricing, large-scale data pipelines, and machine learning products.

The Price Optimization (PO) team is where insights become decisions. We work with large-scale customer data and market predictions - like demand forecasts - to drive revenue management decisions that actually move the needle.

At our core, we build and maintain the decision-making engine. That means designing the data pipelines that bring customer data in, and running it through an optimization engine that simulates the market - weighing competition, pricing constraints, inventory availability, predictive models, and each client's unique business policies - to generate the best possible price recommendations. As the final step before recommendations reach the client, quality, reliability, and attention to detail aren't just nice to have. They're everything.

You will lead the team through architecture decisions, development, and deployment of mission-critical systems-while growing and mentoring a high-performing team.

Responsibilities:

Manage a team of data scientists and data engineers responsible for building robust, scalable, and high-performance data pipelines and infrastructure.
Design, build, and maintain distributed data processing workflows (batch & streaming).
Drive best practices for data quality, validation, testing, and observability.
Own and evolve data architecture in alignment with business and product goals.
Manage sprint planning, task breakdown, code reviews, and performance feedback for your team.
Contribute hands-on to key development tasks and architecture decisions.
Recruit, mentor, and grow the data science engineering team.

We are building a new AI venture inside monday.com to redefine how businesses interact with their customers through next-generation conversational AI and agentic systems. Our AI doesnt just react - it plans, reasons, and acts.

Youll join a small, highly autonomous team with the agility, ownership, and pace of a startup, working alongside world-class engineers and researchers to build the next generation of conversational AI. Youll have access to large-scale real-world data, the compute and resources to pursue groundbreaking research, and the freedom to move fast while helping shape Harmonys AI vision.

What youll do

Research novel algorithms and design new deep learning architectures to advance our in-house NLP and conversational models.

Develop methods for translating customer goals into structured representations with controlled states and real-time observations.

Help design the reasoning layer that orchestrates our AI models efficiently alongside a range of LLMs, enabling each agent to adapt its policy throughout a conversation while remaining aligned with customer objectives.

Build analytical tools that trace our AI decision process across a vast corpus of conversations, providing clear visibility into their reasoning and behavior.

Collaborate closely with engineers and product teams to translate cutting-edge research into production at scale.

Proactively lead new ideas and technical initiatives.