Were looking for a Senior Data Scientist to be a core driver in how our product empowers security teams. You will be expected to deeply understand customer needs and translate them directly into product features that deliver real value. You'll own key parts of our frontend stack, drive key architectural decisions, and turn complex security data into clear, actionable business insights.

In this role, you will design, build, and productionize advanced models that help organizations secure AI systems across data, models, and runtime usage. Youll work closely with Product, Engineering, and Security teams to turn complex, real-world security problems into scalable, high-impact AI solutions.

This is a high-impact, hands-on role with true ownership, where your work directly shapes the intelligence powering a category-defining AI Security platform.


What Youll Do:

Own End-to-End Model Development (Research → Production)

Take full ownership of the model lifecycle: problem definition, research, prototyping, training, evaluation, deployment, and ongoing optimization.

Design and build scalable ML / AI solutions to detect, analyze, and mitigate AI-related security risks.

Ensure models are robust, explainable, and production-ready in real-world enterprise environments.

Partner Deeply with Product & Engineering

Collaborate closely with Product Managers to translate customer pain points and security requirements into clear modeling objectives.

Work hands-on with engineering to integrate models into production systems and data pipelines.

Balance research depth with pragmatic execution and business impact.

Build AI Security Intelligence

Develop capabilities across areas such as AI behavior analysis, anomaly detection, model governance, data risk detection, and usage observability.

Work with structured and unstructured data, including logs, prompts, model outputs, and metadata.

Continuously iterate on models based on usage patterns, feedback, and emerging threat vectors.

Lead Research POCs & Innovation

Stay at the forefront of LLMs, applied ML, and AI security techniques and bring new ideas into the product.

Were looking for a Data scientist Expert to join us and spread the power of our company. As a Data Scientist you will be responsible for driving research and development of autonomous AI agents and LLM-powered systems at our company. You will work closely with cross-functional teams to explore, innovate, and implement AI-driven solutions to tackle emerging threats, examine cloud security features, and enhance the companys security posture.
Responsibilities
Lead applied research on AI agents and LLM-driven features in the company platform - from autonomous threat investigation agents to AI-powered security operations workflows.|Cover a range of features - from leveraging LLMs to enhance customer investigation experience to novel usage of AI for cloud security.
Collaborate with engineering teams to design, build, and maintain production pipelines.
Work closely with the Security Research and Product teams to define research goals.
Conduct experiments and evaluate the performance of AI models, algorithms, and techniques using real-world datasets and simulated environments.
Stay abreast of cutting-edge AI methodologies, frameworks, and tools and apply them to improve security solutions' accuracy, efficiency, and scalability.

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.

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.

We're looking for a Data Scientist to join our fast-growing Data Science team focused on AI-first features. This role sits at the core of how personalizes the sales experience, designing and deploying end-to-end ML models that move real business metrics. You'll collaborate closely with ML engineers, product managers, and data engineers, and join weekly sessions where the team shares research, tests new ideas, and learns together.
Hands-on experience using AI development tools such as Cursor or Claude Code is a must for this role.
we're building for builders. We build fast and AI-first, so we look for builders. By a builder, we mean someone who turns "maybe" into "done".
This role is based in Tel Aviv. We work in a hybrid model, with 3 days a week in the office.

Required Data Scientist
Tel Aviv
Full-Time
About Us:
Were building the first AI-native autonomous revenue engine for D2C brands, a new category of AI infrastructure replacing the entire revenue stack.
If you want to build category-defining infrastructure with a team that ships weekly, lets talk.
About the Role:
As a Data Scientist, youll be at the heart of the intelligence behind our product. Youll develop predictive models, analyze complex behavioral datasets, and collaborate across engineering and product to turn insights into real-time actions for our clients. This is a hands-on role with plenty of ownership and room to grow.
Responsibilities
Model Development:
Design scalable ML models that predict customer churn, ideal purchase timing, product recommendations, and more.
Data Exploration & Feature Engineering:
Structure and clean large datasets, develop features, and surface key behavioral patterns.
Collaborate with Engineering:
Work closely with developers to implement models and ensure performance at scale.
Business Insight Generation:
Turn data into actionable insights that drive product features and client decisions.

We're looking for a Data Scientist to join our team. As a Data Scientist, youll be a key member of our AI team, designing, building, and deploying cutting-edge AI systems that leverage large language models (LLMs), unstructured data, and advanced ML techniques. Youll be instrumental in bringing AI from research to real-world production, delivering high-impact features that drive our security platform.

In this role, you'll have a unique opportunity to solve complex problems, work with large scale data and be part of the core team that shapes the future of AI in the company.


WHAT YOU WILL DO
Design and develop end-to-end AI solutions, from data ingestion and modeling to deployment and observability.
Build and fine-tune LLM-based applications to tackle complex cybersecurity challenges.
Own the full ML lifecycle - from ideation and experimentation to production readiness.
Collaborate with product, engineering, and security teams to turn AI research into user-facing features.
Work with large-scale unstructured data (e.g., logs, threat intel, alerts) to extract meaningful insights.
Evaluate and optimize AI system performance, scalability, and reliability.
Contribute to core architectural decisions related to AI and ML infrastructure.

We are global, with HQ in NYC and R&D centers in Tel Aviv, New York, Finland, Berlin, Belgium and San Diego. We work in a fast-paced environment and have a lot of challenges to solve. If you like to work in a huge scale environment and want to help us build products that have a huge impact on the industry, and the web - then your place is with us.
What you will do:
Develop and improve models that analyze millions of videos and images every day across the web, Smart TVs, YouTube, Facebook, Twitter, Instagram, TikTok and more to detect the content categories they are about.
Work alongside experienced data scientists and engineers in a cutting-edge environment, contributing to advanced ensembles of models at huge scale.
Participate in the full development cycle - from research and experimentation through to deployment - gaining hands-on experience with production ML systems.
Leverage AI-powered tools and assistants as part of your daily workflow to accelerate research, coding, and analysis.
Help advertisers avoid negative or irrelevant content and target what's most relevant to their brand, keeping the web free for everyone.

we are looking for a Data Scientist.
This is a high-impact, algorithm-focused Data Science role for a sharp ML practitioner who lives at the intersection of recommendation systems, user psychology, and feedback loops. As our Match Quality & Feedback Loops Expert, you will own the algorithmic core that powers meaningful connections on our platform. You are not here to just build models in isolation; you are here to continuous-tune evaluation metrics, solve cold-start and balance problems, and optimize real-time feedback loops that drive true user satisfaction, engagement, and long-term retention.
What You'll Do:
Algorithmic Match Quality: Design, train, and deploy production ML/AI models for recommendation engines, candidate ranking, and personalization to maximize match quality and user satisfaction.
Feedback Loop Optimization: Build and refine implicit and explicit feedback mechanisms (likes, messaging patterns, churn/retention signals) to continuously evolve algorithmic performance in real time.
Metric Frameworks & Evaluation: Define and implement robust online and offline evaluation frameworks, moving beyond naive accuracy metrics to measure long-term ecosystem health, fairness, and engagement.
Cold-Start & Liquidity Optimization: Develop innovative strategies to address cold-start problems for new users and balance marketplace liquidity across different geographic and demographic cohorts.
Cross-Functional Collaboration: Work hand-in-hand with Product Managers, Data Engineers, and Core AI/ML teams to translate complex behavioral insights into actionable product features.

Were looking for a sharp and driven Product Data Scientist to join our fast - paced Data Labs team.
As part of a high-performing group of analysts, youll handle complex, custom requests from some of the biggest names in the market, turning raw data into strategic, ad hoc insights.
The work is intense and constantly evolving - it requires strong analytical skills and the ability to work independently under pressure.
Youll need to be curious, adaptable, and willing to dive deep to find answers where others might stop. If you thrive in a demanding environment and are excited by the opportunity to make a real impact, we want you on our team.
What does the day-to-day of a Product Data Science Customer Facing (Data Labs) look like:
Building custom-made reports end to end - from meeting with the client and understanding their needs, to writing the code and setting up the report for ongoing delivery.
Apply your expertise in quantitative analysis and data mining to turn data into insights.
Conduct research and develop tools that will help answer clients business questions by using our raw data sets and algorithms.
Partner with Engineering teams to establish an infrastructure to scale solutions.
Partner with the Advisory Services team of Consultants to answer strategic business questions and deliver custom data products seamlessly.