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We are on the search for a Marketing Analytics Lead who will join our Data team in Tel Aviv. As a Marketing Analytics Lead in a Data-Driven company, you will have a significant opportunity for impact and drive the company to new heights. You will influence decision-making processes throughout marketing budget decisions, new user journeys, be a partner to cross-functional teams within data, marketing & Top of Funnel, and drive strategic business decisions that shape the direction of the company.
Here are a few of the things you will do:
Own end-to-end analytics for marketing and product growth initiatives, directly supporting business strategy and growth, including and not limited to acquisition, lifecycle, and user onboarding.
Act as the primary data owner for the planning, monitoring, and measuring a variety of marketing initiatives, ensuring accuracy, consistency, and trust in decision-making across stakeholders, enabling your stakeholders to learn from data and iterate with confidence.
Translate complex datasets from multiple sources into clear, actionable insights with measurable business impact.
Proactively initiate and perform ad hoc research and deep-dive analyses to surface unknown business opportunities to inform strategic and operational decisions.
Partner with marketing, product, finance and company leadership to drive cross-functional, data-driven outcomes.
Design, improve, and scale analytics infrastructure, data pipelines, and workflows to suit your analytics needs; work hands-on using tools such as SQL, DBT, Looker, and partner closely with Data Engineering and Data Science teams.
Design, execute, and evaluate A/B tests using rigorous statistical methods and well-defined KPIs, including ownership of appropriate KPI selection.
Present insights and recommendations to senior stakeholders with clarity and influence, through written communication, presentations, and via dashboards.
Contribute expertise to shared analytics standards, best practices, and knowledge forums (e.g., Data Guild).

Were looking for a Data & Analytics Team Lead to manage and grow our data team and own the data layer behind our AI. Youll lead a team of data analysts responsible for neural-network model analysis, model performance tracking, customer-facing and internal BI. Youll act as both the people manager and the technical lead for the team, setting technical direction while staying hands-on.
Youll thrive in this role if youre passionate about turning data into better AI products, enjoy solving complex analytical problems, and like working at the intersection of Data, Analytics, and Artificial Intelligence.
Responsibilities:
Lead the data strategy supporting AI model development, evaluation, and continuous improvement
Define KPIs and monitoring frameworks for AI model performance.
Analyze NN model outputs, build and maintain model-tracking and performance-evaluation workflows
Drive close calibration with the Algo, Product, and Data Engineering teams to align data definitions, pipelines, and metrics
Stay hands-on with SQL, Python, BI tooling, and the modern data stack
Build and own agentic data workflows - designing the context, tooling, and data access that let AI agents reliably query, analyze, and act on company data

As Head of Analytics, youll lead the analytics team and strengthen how data is used to support decision-making across the company. Reporting to the VP of Data & Analytics, youll translate the broader data strategy into clear priorities, high-quality analytical delivery, and measurable business impact.

Youll manage and develop teams of analysts and BI, partner closely with senior stakeholders across Product, Sales, Marketing, Finance, Customer Success, and Operations, and ensure that the company has trusted metrics, actionable insights, and scalable analytical capabilities.

This is a strategic and hands-on leadership role. Youll be expected to set direction, create structure, raise analytical standards, and remain closely involved in the companys most important business questions.

Youre welcome to work in our offices in Tel Aviv, Israel

Your responsibilities will include:

Team leadership and development. Lead, mentor, and develop the analytics team. Set clear expectations, establish ownership, support professional growth, and create a high-performance culture focused on business impact, analytical quality, and accountability.
Analytics strategy execution. Partner with the VP of Data & Analytics to shape the analytics strategy and own its execution, prioritization, and delivery. Translate company goals into a clear analytics roadmap and ensure resources are focused on the highest-impact business needs.
Business partnership. Act as a trusted analytical partner to senior leaders across Product, Sales, Marketing, Finance, Customer Success, and Operations. Understand their objectives, challenge assumptions, and help turn strategic questions into measurable decisions and actions.
Decision support and advanced analysis. Lead high-impact analyses across customer behavior, product performance, revenue, retention, pipeline, operational efficiency, and business growth. Ensure findings are translated into clear recommendations rather than presented as data alone.
Metrics and analytical governance. Establish and maintain consistent KPI definitions, business logic, and analytical standards. Ensure stakeholders use trusted and aligned metrics across dashboards, reports, forecasts, and business reviews.
Dashboard and reporting oversight. Guide the design, implementation, and improvement of executive and operational dashboards. Ensure reporting is relevant, reliable, easy to use, and aligned with business priorities.
Self-service analytics. Enable business teams to access and use data independently while maintaining appropriate governance, security, quality, and consistency. Identify where self-service creates value and where centralized analytical support is required.
AI-driven analytics. Help define and implement AI-assisted analytics capabilities that reduce manual reporting, accelerate insight generation, support natural-language access to data, and proactively surface risks or anomalies. Establish clear quality and validation standards for AI-generated outputs.
Cross-functional data collaboration. Work closely with Data Engineering, Data Architecture, and other technical teams to ensure that analytical datasets, semantic models, and data pipelines support current and future business requirements.
Operating model and prioritization. Build scalable processes for intake, prioritization, delivery, documentation, and stakeholder communication. Balance urgent business requests with strategic initiatives and long-term capability development.

we are seeking a Senior Data Analyst position to join the BI Team, with a passion for technology, to solve unique problems within our measurements. Our team solves many challenges in turning raw data into accurate signals and extracting insights to improve the 365Scores products. Appropriate candidates have an understanding of multiple components across the big data stack: large-scale data analysis, data quality, statistics, and visualization. If you are the kind of researcher who's focused on results and a quick learner, this role is for you. This position is located in our Tel Aviv office.

Responsibilities
Function as the data authority in the Monetization domain - performing ad-hoc research and analysis on the company's rich data to support unique and strategic business questions.
Define, analyze, and monitor KPIs and OKR metrics to continually improve company products.
Analyze large, complex data sets to address strategic and operational business questions.
Actively take part in building and maintaining our AI Driven-BI Agentic Architecture.
Build dashboards and visualizations to answer key questions for the company's in-house various teams, specifically for the Monetization Team.
Perform qualitative, quantitative, and statistical analysis.
True passion for understanding data and finding Insights.
Provide actionable recommendations and conclusions from data to shape features and future product road maps.

Required Senior BI Analyst
About the role:
Data only creates value when people can see it, trust it, and act on it. As Senior BI Analyst, you own that last mile: the BI platform everyone opens to answer their questions, and the KPI definitions that make sure the numbers on every dashboard mean the same thing across every team.
This is the business-facing anchor of our analytics function. You'll build and govern the reporting layer, define the metrics that leadership runs the company on, and lead the Business Analyst guild - the network of domain analysts embedded across GTM, Finance, CS, and Product. You're equal parts platform owner, metrics authority, and enabler of the analysts around you.
If you love turning messy business questions into clear, trusted, self-serve answers - and raising the analytical bar for a whole company while you do it - this role is for you.
What youll own:
Own the BI platform end-to-end - Design and manage the dashboard architecture, set standards for report building and certification, manage access/governance, and keep the platform performant and trusted
Define and govern company-wide KPI metrics - Build a certified KPI catalog with documented logic and ownership; arbitrate metric definitions across teams so "win rate" means the same thing everywhere and is encoded once in the semantic layer
Drive self-serve analytics adoption - Empower stakeholders to answer their own questions by making the platform accessible, intuitive, and built on trusted definitions
Co-lead the Analytics guild - Convene and lead the company-wide community of practice connecting domain analysts; run enablement, tooling decisions, and reviews to keep everyone aligned on standards and the certified KPI catalog
Bridge analytics and engineering - Partner with the AI Data Engineer to ensure business definitions translate consistently into technical implementations across dashboards and AI agents
What you'll do day to day:
Design, build, and maintain governed dashboards and reports that stakeholders actually use.
Curate the certified KPI catalog - definitions, logic, ownership, and change control.
Partner with GTM, Finance, CS, and Product to translate business questions into clear, reusable metrics.
Drive self-serve BI adoption and reduce ad-hoc reporting requests.
Run the Business Analyst guild: standards, reviews, enablement, and tooling.
Work with data engineering to keep KPI definitions aligned with the semantic layer and underlying models.
Own the health of the BI platform: access, performance, certification, and cleanup.

We are looking for a highly analytical, deeply technical, and proactive Senior Salesforce and Business Applications Analyst to join our team. In this role, you will champion an AI-first approach, leveraging AI across every aspect of your work to optimize efficiency and drive innovation.
You will bridge the gap between business needs and technical execution, taking full ownership of complex systems and driving end-to-end processes. Your focus will be on supporting, enhancing, and automating our operations across various business domains, including Sales, Service, and Marketing.
This hands-on role encompasses managing daily system maintenance, configuring systems, integrating AI-driven workflows, and overseeing projects from inception to completion.
Key Responsibilities:
End-to-End Project Management: Manage complex, cross-functional projects from initial ideation, through requirements gathering, to successful deployment and optimization.
Drive Innovation & Initiative: Act as a proactive change-agent. Identify business gaps, propose innovative solutions, and passionately push new initiatives forward to improve efficiency and performance.
System Ownership: Take full accountability and end-to-end ownership of the systems health, functionality, and alignment with business goals.
Mentorship & Leadership: Guide, mentor, and upskill junior team members, fostering a culture of continuous learning and professional excellence within the team.

This is a full-time on-site role for an AI Data Analyst, located in the Tel Aviv District, Israel. The AI Data Analyst will be responsible for analyzing data, developing data models, conducting statistical analysis, and communicating findings to relevant stakeholders. Daily tasks will include interpreting complex data sets, generating actionable insights through data analytics, and supporting the development of AI-powered compliance solutions.

We are looking for a Senior Fraud Analyst to serve as the technical cornerstone of our Fraud Prevention team.
In this role, you won't be managing a team; youll be managing the technical evolution of our fraud defenses. Reporting directly to the Fraud Prevention Director, you will act as a high-level individual contributor, bridging the gap between data science, engineering, and risk strategy. You will be responsible for pioneering the use of AI and advanced analytics to protect our community and ensure our platform remains the safest place for independent businesses to grow.
Here are a few of the things you'll do:
Technical Strategy & Architecture: Partner with the Fraud Prevention Director to define the long-term technical roadmap, moving us toward an AI-first, autonomous fraud detection ecosystem.
AI & LLM Integration: Design and implement Generative AI agents and LLM-powered workflows to automate complex forensic investigations, reducing the time-to-detect for emerging fraud vectors.
Advanced Detection Modeling: Develop and prototype sophisticated ML models and graph-based heuristics to identify collusion, synthetic identities, and fraud rings.
Cross-Functional Technical Lead: Serve as the primary technical consultant to Product and Engineering, ensuring that new payment features (like RTP or international expansion) are built with scalable, AI-driven safeguards from day one.
Expert Forensics: Act as an escalation point on high-stakes, large-scale fraud attacks, utilizing advanced Python and network analytics to deconstruct and mitigate threats.
Data Excellence: Set the standard for the fraud teams technical stack. You will optimize our SQL/Python environments and ensure our data infrastructure is capable of supporting real-time AI inference.