לוח משרות דרושים Senior Data Analyst בפתח תקווה

we are looking for a Senior Data Analyst to join our growing Analytics & Growth team and play a key role in tracking, analyzing, and optimizing the companys overall performance across customers.
The role focuses on defining event tracking, attributes, and properties mapping, analyzing conversion funnels, and identifying trends or issues using web analytics tools. You will work closely with R&D, Professional Services, Product managers, and the Business Intelligence team to ensure data integrity, validate tracking implementations, support new feature launches, and enable data-driven decision-making across the organization.
The ideal candidate is highly independent, curious, and proactive, with a strong drive to uncover root causes and continuously learn new tools and methods to solve complex analytical challenges
Define, implement, and maintain event tracking, attributes, and properties across web and product platforms
Gather and analyze data from multiple sources, including web analytics, internal systems, session recordings, and online browsing activities
Conduct in-depth analyses of customers conversion funnels and trends to identify optimization opportunities, as well as raise alerts and potential issues
Monitor KPIs related to conversion, engagement, and overall company performance
Guide and support our e-commerce funnel optimization with data backed insights.
Collaborate with R&D, product managers, and cross-functional teams to define tracking needs, raise alerts, and support new feature launches
Ensure web analytics data is accurately reflected in BI dashboards and reports, enabling reliable decision-making and insights
Work closely with the BI team on reporting requests, dashboards design, QA, and acceptance before release
Provide actionable, data-backed insights to support company-wide strategy and analytical projects
Take initiative to learn independently, adopt new analytical approaches, and work autonomously on complex problems.

As a Senior Product Analyst at our company, 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.

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 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.

As a hybrid analyst-data scientist, youll partner closely with Customer Success, Professional Services, Training, and Support teams to deliver both advanced modelling, and foundational analyses. Youll uncover patterns, build models, and translate complete findings into clear, actionable recommendations that influence senior leadership decisions and improve Enterprise customer outcomes.
If you thrive on uncovering patterns in data, influencing high-level business strategy, and translating insights into measurable customer outcomes, this role is for you.
Responsibilities:
Work as part of a small Customer Success Insights and Operations team that leads data analysis, predictive insights and operational support to a growing CS team dedicated to the success of our customers.
Deliver actionable analyses and insights across key Enterprise CS OKRs, initiatives and growth experiments - leading 2-3 strategic projects per Quarter. These projects could be anything from churn analysis, expansion-likelihood modelling, behaviour clustering, to NPS sentiment and customer success plan performance.
Build, test and maintain predictive and statistical data models that identify risk, quantify revenue opportunities and prioritise CS actions at scale.
Support the creation of dashboards with our BI team that track customer health, renewal risk, and engagement impact across our enterprise accounts.
Design and analyse growth and expansion experiments to identify and scale opportunities for product adoption and usage expansion.
Partner with CS leadership to support MBRs/QBRs, operational reviews, and executive reporting.
Drive cross-functional collaboration with Product, Sales, and Marketing to ensure alignment on customer insights and opportunity areas.
Respond to specific internal CS requests to support customer retention and growth plays, delivering 5+ high-value analyses monthly that fuel CS OKRs and strategic decision-making.
Leverage statistical and analytical tools (e.g., SQL, Python, statistical / ML libraries as well as BI tools like Qlik) to model data, test hypotheses, and communicate recommendations with clarity and impact.
Explore and help operationalise the use of AI-tools like ChatGPT and Google Gemini to support analysis velocity, identify patterns and automate insights generation.
Champion data quality and governance, ensuring reliable and scalable data pipelines in partnership with MIS and Data Engineering teams.
Advise on KPI design and performance tracking for Enterprise CS metrics including NRR, GRR, churn, and adoption health scores.