דרושים » תוכנה » Fraud Data Scientist

We are seeking a talented and motivated Data Scientist for a temporary position to support our growing data, analytics, and AI automation needs. This role focuses on turning large volumes of data into models, insights, and intelligent automation - combining classic data science (statistical analysis, feature engineering, machine learning) with the emerging Agentic AI stack (LLMs, MCP, agent orchestration). You will work closely with data engineers and internal teams to prototype and productionise models, build LLM-powered agents and workflows, and support the integration of AI capabilities across the organization.

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 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.

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 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.

As a Senior Data Scientist , you will be an integral part of our Machine Learning and AI team. The role is hands-on and impact-driven, focusing on building, improving, and delivering machine learning models that directly support business goals.

Responsibilities
Design and deploy production ML systems that drive automated business decisions (pricing, bidding, resource allocation)
Build end-to-end ML pipelines - from data ingestion and model training to serving, monitoring, and incident response
Translate ambiguous business problems into rigorous mathematical frameworks and own them from conception to production impact
Conduct rigorous experimentation (A/B testing, causal inference, uplift modeling) to measure and improve model performance
Maintain and improve real-time models that adapt to incoming data and feedback signals
Mentor junior team members on ML best practices and production standards

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 looking for a talented and experienced Data Scientist to join our Research Data Science team and play a key role in shaping the future of cloud-native network security. Your primary mission will be to lead the development and deployment of AI-driven capabilities that protect enterprise networks at scale through Catos SASE platform, powering core products such as our AI assitant, DLP, XDR, IPS, and more.
Leveraging rich, real-time data from our global backbone and Cloud data warehouse, you will apply advanced reserach analytics, machine learning, deep learning and GenAI techniques to solve complex cybersecurity and networking challenges.


This is an exciting opportunity to join a fast-growing company and drive innovation in the rapidly evolving SASE space.



Key Responsibilities

Lead the design, development, and deployment of AI/ML models that enhance Catos security and networking products
Leading networking and security research, including analysis of large-scale network traffic and security data to identify patterns, threats, and opportunities for product improvement
Research, fine-tune, and train models optimized for real-time inline inference under limited compute resources
Collaborate cross-functionally with product, engineering, and support teams to translate product and business needs into AI solutions
Define and track success metrics to ensure AI solutions meet performance and business goals

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 hiring an exceptional Applied AI Scientist to join our team!
In this role, you'll design and deploy enterprise-grade AI agents that drive real business impact across core functions - Sales, Marketing, Customer Success, Customer Support, Risk, and Finance. You'll be building agentic systems that execute complex, multi-step business workflows end-to-end. The ideal candidate is a hands-on builder with deep AI expertise who thrives on turning complex business problems into reliable, production-grade AI systems.
In This Role, You Will Be Responsible For:
Enterprise AI Agent Development: Designing, building, and deploying AI agents that automate and augment high-value workflows across business functions - including lead qualification and outreach (Sales & Marketing), churn reduction(Customer Success), and Ticket deflection (Support).
Agentic Architecture & Orchestration: Owning the end-to-end agent stack - from tool use, memory management, and multi-step planning to human-in-the-loop escalation patterns, guardrails, and audit trails suited for an enterprise fintech environment.
Knowledge Systems: Building and maintaining RAG pipelines that ground agents in Tipalti's proprietary knowledge - product documentation, customer data, financial records, and internal playbooks - using vector databases, hybrid search, and re-ranking.
Evaluation & Continuous Improvement: Defining agent evaluation frameworks that measure task completion, accuracy, hallucination rates, latency, and business impact - then iterating on agent behavior based on real usage data and stakeholder feedback.
Cross-Functional Collaboration: Partnering with stakeholders across the company to define agentic use cases, translate business requirements into technical features, and deliver products that create measurable ROI - from data preprocessing through product deployment.

We're looking for a Machine Learning Team Lead to own real parts of it.
What you'll actually do?
Lead, mentor, and grow a multidisciplinary team composed of Data Scientists, Data Analysts, and DLP Analysts.
Define and lead the team's technical vision and execution strategy, driving technical excellence and ensuring alignment with business priorities and product objectives.
Oversee the design, development, validation, and deployment of advanced machine learning solutions for customer-facing products.
Hands-on ownership of current AI services.
Establish and enforce best practices for model development, experimentation, evaluation, documentation, and code quality.
Collaborate closely with Product Managers, Data Engineers, Software Engineers, and domain experts to translate business challenges into scalable ML solutions.
Drive execution and delivery, balancing innovation, technical quality, and time-to-market considerations.
Promote operational excellence by improving the reliability, scalability, and maintainability of production machine learning systems.
Establish scalable engineering processes, workflows, and best practices.
Lead the team transformation from an early-stage organisation into a mature, production-grade AI engineering team.