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Analytics team lead | Fintech | Direct Placement Location: Tel Aviv | Hybrid Model We are seeking a strategic and impact-driven Analytics team lead to join a fast-growing Fintech company. This is a Direct Employment opportunity from day one, offering a leadership role in a highly dynamic and evolving business environment.
Key Responsibilities As the team lead, you will orchestrate the sprint cycles and backlog for a diverse group of over 5 analysts, ensuring high-speed delivery in a fast-paced setting. You will be responsible for cultivating analytical rigor through advanced A/B testing methodologies and standardized frameworks, while continuously auditing internal workflows to eliminate manual inefficiencies. Your role involves defining and owning departmental North Star metrics, proactively educating stakeholders on business drivers, and maintaining a hands-on approach to ensure complex, cross-functional projects meet their milestones. Additionally, you will champion the integration of AI tools and frameworks to accelerate the teams ability to generate rapid, actionable insights.

We are seeking a Director of Analytics to lead analytics-driven growth initiatives across our business. This role is highly strategic and hands-on, combining customer-facing leadership, business optimization, and advanced analytics.
The Director of Analytics will partner closely with Customer Success Managers (CSMs), Sales Leaders, the CRO and the leadership team to drive revenue growth, customer acquisition, as well as performance optimization across pre-sales and post-sales.
This role requires an exceptional communicator with strong business acumen, deep analytical capabilities, and proven experience leading high-performing analytics teams in a complex data environment.
Responsibilities:
Lead analytics-driven growth initiatives focused on customer acquisition, expansion, and monetization.
Partner closely with the CRO, Sales leadership, and Customer Success Managers to identify growth levers, support customers analytics requests, and optimize revenue and Conversion rates performance.
Manage and develop a high-performing analytics team, setting clear expectations for analytical rigor, problem definition, and insight storytelling
Coach and mentor analysts with a strong focus on business impact and customer-facing insight delivery
Act as a customer-facing analytics leader, participating in QBRs, executive reviews, and strategic customer conversations
Own the customer and sales data domain, including metric definitions, data consistency, and integrity
Proactively identify, troubleshoot, and resolve data quality and data reliability issues in partnership with BI, R&D, and Product
Work closely with Product and R&D teams to influence roadmap decisions through data and customer insights
Define KPIs, dashboards, and measurement frameworks that align analytics output with business outcomes
Independently initiate and lead cross-functional analytics projects from concept through delivery and impact measurement
Support pre-sales processes with analytics, including customer insights, benchmarking, ROI and value modeling, and data-backed sales narratives.
Support post-sales processes with analytics, including customer monitoring, proposition suggestion and optimization analysis.

We are seeking a Senior Data Scientist to be one of the first data science hires for our newly formed ML team. This is a unique ground-floor opportunity to build our data science capabilities from scratch and have direct influence on our analytical and modeling approaches. This role combines advanced data science expertise with foundational contributions, requiring someone who can develop sophisticated models, conduct deep analytical research, and help establish the data science methodologies that will guide the team as we scale. As one of our founding data scientists, you'll work closely with our Tech Lead to shape our modeling approaches, define our analytical standards, and build the fundamental data science skill set for future hires.
What You'll Do:
Build foundational data science capabilities: As one of our first data science hires, work with the Tech Lead to develop core modeling methodologies, analytical frameworks, and research practices
End-to-end model development: Take ownership of complete ML model lifecycle - from initial research and experimentation through production deployment and monitoring
Build impactful models: Design, develop, and deploy machine learning models that solve complex business problems across payments, risk, and customer analytics
Define analytical standards: Help establish best practices for data exploration, feature engineering, model validation, and statistical analysis
Conduct deep research: Lead exploratory data analysis and research initiatives to uncover insights and identify ML opportunities across the business
Partner with stakeholders: Work closely with business teams to understand requirements, translate problems into data science solutions, and communicate findings effectively
Establish model development practices: Help set up our approach to model experimentation, A/B testing, and performance monitoring
Shape data science culture: Contribute to establishing the team's analytical rigor, documentation standards, and knowledge-sharing practices
Drive innovation: Research and evaluate new ML techniques, algorithms, and approaches that could benefit our business use cases.

Required data science manager - ai solutions
company description
A palo alto networks company, is the global leader in identity security, trusted by organizations around the world to secure human and machine identities in the modern enterprise. Our ai-powered identity security platform applies intelligent privilege controls to every identity with continuous threat prevention, detection and response across the identity lifecycle. with identity security, organizations can reduce operational and security risks by enabling zero trust and least privilege with complete visibility, empowering all users and identities, including workforce, it, developers and machines, to securely access any resource, located anywhere, from everywhere.
job description:
as a data science manager at palo alto, you will lead a high-performing team developing ai/ml solutions that secure the digital worlds most sensitive assets. youll play a key role in driving innovation, productizing Machine Learning systems, and applying advanced modeling techniques to real-world cybersecurity challenges.
in this leadership role, youll balance hands-on technical involvement with strategic oversight, guiding projects from research to production. youll work closely with data scientists, engineers, analysts, product managers, and cyber-security researchers to build intelligent features across our identity security portfolio
lead, mentor, and grow a team of applied data scientists working on Machine Learning models that power ai-driven cybersecurity solutions.
own the end-to-end development lifecycle of ai projects - from exploratory research and experimentation through scalable deployment and optimization.
partner with engineering and product leadership to define technical strategies, prioritize initiatives, and ensure successful model delivery.
drive innovation across a broad spectrum of ml domains including supervised/unsupervised learning, anomaly detection and generative ai.
provide hands-on guidance in model development using tools such as scikit-learn, pytorch, tensorflow, and hugging face. - ensure high-quality execution through strong code review practices, reproducibility, and model evaluation frameworks.
champion best practices in mlops, data governance, explainability, and monitoring.
keep pace with academic and industry advances and translate cutting-edge research into productized capabilities.

a palo alto networks company, is the global leader in identity security, trusted by organizations around the world to secure human and machine identities in the modern enterprise. ai-powered identity security platform applies intelligent privilege controls to every identity with continuous threat prevention, detection and response across the identity lifecycle. with identity security, organizations can reduce operational and security risks by enabling zero trust and least privilege with complete visibility, empowering all users and identities, including workforce, it, developers and machines, to securely access any resource, located anywhere, from everywhere.
job description:
as a senior Product Analyst , youll join the ai solutions group, contributing to the development of intelligent identity security capabilities. this role sits at the intersection of data, product, and ai - giving you the opportunity to apply analytical thinking and technical skills to help shape real-world solutions. youll work alongside senior analysts, data scientists, engineers, and product managers to explore data, derive insights, and contribute to productizing ai-driven features that improve the performance, usability, and intelligence of our offerings. analyze product usage and behavioral data to support the design and improvement of ai-powered features.
work closely with product managers and engineers to translate insights into productized solutions that enhance functionality and User Experience.
build and maintain dashboards, kpis, and reports that drive product decision-making.
contribute to the development and validation of success metrics for new capabilities.
collaborate with data scientists on experiments, a/b tests, and model monitoring efforts.
ensure data quality and support scalable pipelines by working with data engineering teams.
communicate findings through clear presentations and visualizations that influence roadmap decisions.
develop a deep understanding of product workflows and user behavior to guide analytical priorities.

Required Staff Data Analyst, Risk & Fraud
Job Overview
As a Staff Analyst on the Trust and Safety Analytics team, you will be responsible for identifying, making available, and leveraging critical data elements to optimize our ability to fight fraud, protect its customers and enforce acceptable use of products and services. Specifically, you will focus on applying your analytical skills to design, support and scale tools, processes, and strategies that proactively identify and mitigate risks across the organization.
Responsibilities:
Collaborate closely with Engineering and Product teams to design, implement, and maintain analytics frameworks, tools, and data systems that support effective data monitoring and risk management strategies, enabling informed, data-driven decision-making.
Take an active role in the analytics team's efforts to manage and enhance Trust and Safety platform capabilities. Provide timely insights and actionable recommendations to strengthen platform performance and address emerging challenges. Develop tools and systems to measure platform health and assess risks, including designing dashboards to track performance metrics, analyze trends, and identify areas that require attention or intervention.
Ensure analytics systems are consistently reliable, accurate, and available. Establish proactive monitoring processes and implement thorough testing to detect and address issues, minimizing system disruptions or delays.
Contribute to effective incident management by using analytics to identify root causes, provide actionable insights, and continuously improve platform risk mitigation solutions.
Stay abreast of the latest developments in AI, and integrate insights into your analysis to address emerging risks.

Required Senior Data Analyst, Risk & Fraud
Job Overview
As a Senior Analyst on the Trust and Safety Analytics team, you will play a critical role in identifying, analyzing, and operationalizing key data signals to help us prevent fraud, protect customers, and enforce acceptable use of products and services. You will apply strong analytical and technical skills to support and scale risk detection tools, monitoring processes, and mitigation strategies across Trust & Safety. This role partners closely with Product, Engineering, and Operations teams to deliver insights that drive data-informed decisions and measurable risk reduction.
Responsibilities:
Partner with Engineering and Product teams to support the design, implementation, and maintenance of analytics tools, dashboards, and data pipelines that enable effective fraud and risk monitoring.
Analyze large, complex datasets to identify trends, anomalies, and emerging fraud patterns, translating findings into actionable recommendations.
Contribute to the ongoing improvement of Trust & Safety platforms, including monitoring performance metrics, assessing platform health, and identifying risk gaps or degradation.
Design and maintain dashboards and reporting (e.g., Tableau) to track fraud performance, operational efficiency, and risk exposure.
Ensure data quality and reliability by performing validation, testing, and monitoring of analytics outputs; proactively identify and escalate issues.
Support incident analysis and investigations by using data to identify root causes, quantify impact, and recommend mitigation actions.
Stay current on fraud trends, AI-driven abuse, and industry best practices, incorporating new insights into analyses and detection strategies.
Clearly communicate insights to both technical and non-technical stakeholders, influencing decisions through data-backed storytelling.

We are looking for a highly skilled Data Engineer . to build and maintain robust, scalable data pipelines and data marts acting as the connective tissue for intelligence insights generation that serves executive stakeholders , internal customers and 3rd party
The Fintech AI & Data group is looking for a staff Data Engineer to work closely with analysts, data scientists, and software developers and strengthen Fintech by building data capabilities and AI transformation.
Responsibilities:
Gather data needs from internal customers like product and analysts, and translate those requirements into a working database and analytic software.
Design, build, and maintain scalable, reliable batch and real time data pipelines, data marts and warehouse supporting executive dashboards, operational analytics, and internal customer use cases
Ensure high data quality, observability, reliability, and governance across all data assets
Optimize data models for performance, cost-efficiency, and scalability
Develop data-centric software using leading-edge big data technologies.
Build data capabilities that enable automated agentic insights and decision intelligence
Develop reusable data services and APIs that power AI-driven workflows
Evolve our data architecture into an AI-native data layer designed to power LLMs, AI agents, and intelligent applications
Collaborate with analytics, product, and AI teams to translate business needs into scalable data solutions
Influence the software architecture and working procedures for building data and analytics
Work bBe the go-to person for anything and everything regarding understanding the data - exploration, pipelines, analytics, etc. and work both independently and as part of a team
How youll succeed
Have an impact on satisfying customers and reducing financial fraud
Help build the team by hiring the best talent
Contribute toexperiments and research on how to enhance our capabilities
Learn new technologies and methodologies
Collaborate with other data engineers, analysts, data scientists and developers
Be proactive with a self-starter attitude
Be a good listener, while also having strong opinions on what is right
Be fun to be around :)