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We are looking for an Equity Manager to join our Team.
What does the day-to-day of an Equity Manager look like:
Equity focal point for Finance, Legal, and HR aspects.
Administer all aspects of the companys equity plan (including new grants, vestings, exercises, releases, cancellations, forfeitures, ESPP plan, mobility).
Maintain the integrity of the equity database with the 3rd party Stock Plan Administrator, and manage the day-to-day relationship with that provider.
Oversee the daily activity following exercises and releases, i.e., proper tax withholding, reporting to local payroll, and accurate fund disbursements.
Perform month-end closing procedures and assist with public reporting according to ASC718 Stock-based Compensation.
Manage all tax aspects in the various jurisdictions related to equity.
Perform presentations/training sessions to the companys employees.
Ensure compliance with statutory requirements and manage SOX controls and blackout periods.
This role will include some other responsibilities in the Finance Team outside of Equity.

Responsibilities:
Lead product and feature launches end-to-end: narrative, naming, enablement, web, press, and the launch moment itself.
Own analyst relations, including managing relationships with firms, coordinating briefings and inquiries
Conduct win/loss interviews, competitive analysis, and customer research to sharpen positioning and keep the team ahead of market shifts
Own competitive intelligence, monitoring market trends and adapting messaging to stay ahead in our space
Collaborate closely with Product, Sales and Marketing to ensure a unified narrative across the funnel
Build the sales enablement layer from the ground up: pitch decks, demo narratives, battle cards, one-pagers, discovery guides, and customer proof points.

We are looking for the person who will stand up Jazz's data platform end to end - ingestion, modeling, warehouse, orchestration, cost control - and then turn it into the numbers the company actually runs on: the executive metric set, the GTM and pipeline view, and delivery reporting for R&D.

Owning the platform is a huge part of this role, but success is about more than just keeping pipelines green. You'll partner directly with execs, R&D, and sales to agree on core metric definitions, then make sure everyone across the company can easily get the data they need on their own.



What you'll do

Build the platform from zero. Design and implement the databases, ELT/ETL pipelines and orchestration on a medallion architecture that other people can safely build on top of.
Own the gold layer as the single source of truth. Modeled, tested, documented and trusted, the layer the company argues from, not about.
Define the company's metrics. Work with leadership to define organizational KPIs, instrument them, and keep the definitions honest as the business changes.
Build dashboards that executives actually use. Take complex, multi-source data and make it legible to a C-level reader in thirty seconds.
Serve every BI consumer at Jazz. Sales and GTM (pipeline, funnel, forecast, Salesforce data), R&D (delivery, quality, product usage), Finance and Operations.
Run it in production, at scale. Reliability, data quality, alerting and monitoring, including active tracking and reduction of infrastructure and warehouse costs.
Set the standards. Modeling conventions, testing, documentation, access control, and how BI requests get intake and prioritized.
Make things happen across the org. Present, persuade, and drive alignment between stakeholders who define the same metric three different ways.
Work with AI as a multiplier. We expect heavy, deliberate use of AI in how you build, model, investigate and enable others.

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.

Were looking for a Data Engineer with a strong applied ML focus to join our R&D department!
Why is this role so important?
Our Retail Intelligence products help leading brands and retailers understand how their products, brands and categories perform online. Behind them is data collected from retailers and marketplaces around the world: product pages, brands and categories, each described differently by every site.
Your mission is to turn that data into a single, trusted view: classifying products into a unified taxonomy, normalizing brands and attributes, and matching the same entities across sources. And doing it at scale, across a catalog of more than a billion records that keeps growing and changing every day.
This is an applied ML role within data engineering. Youll build with LLMs, agentic frameworks such as LangGraph, embeddings and classical ML, and ship them as production pipelines. Its hands-on work, not research for its own sake, but it takes a real understanding of classification and NLP methods to choose the right tool for each problem and prove that it works.
So, what will you be doing all day?
Your daily responsibilities may include:
Designing and building LLM-powered and ML-based pipelines that classify, normalize, structure and match product, brand and category data
Building agentic workflows (LangGraph or similar) that automate complex data tasks end to end
Choosing the right approach for each problem (LLMs, embeddings, fine-tuned models, classical classifiers or rules), balancing accuracy, cost and latency
Scaling solutions to run efficiently over billions of records, using Spark, Databricks and our cloud infrastructure
Building evaluation frameworks: ground-truth datasets, labeling processes, quality metrics and ongoing monitoring
Taking solutions from POC to production, and owning them after launch
Working closely with Product to define requirements and shape the roadmap
Collaborating with data engineers, data scientists and other R&D teams on infrastructure and best practices.

Required Senior Security Researcher
Description
About us
We are building autonomous AI hackers that think like the world's best offensive security experts, act like them, and then help fix what they find before the real ones do. If this mission speaks to you, come defend the world's software: autonomously, continuously, and in-depth.
About the role:
This is a rare opportunity to work at the intersection of offensive security and AI - and to have your expertise shape a platform used at enterprise scale. As an Security Researcher, you will push the boundaries of what autonomous agents can achieve.
Your goal is to conduct cutting-edge research into novel attack vectors and vulnerabilities, using those insights to both sharpen our AI and lead the industry conversation on AI-driven security. Youll work alongside a tight-knit team building excellent software in the security space.
Responsibilites
Original Research: Develop new attack strategies and offensive testing techniques for web, network and AI targets, and translate real-world knowledge into improvements for the AI agent
Thought Leadership: Produce high-quality technical content, including research papers, stage demonstrations, or technical blog posts that showcase our unique capabilities and security philosophy.
Public Advocacy: Represent our research at major security conferences and industry events.
AI Enhancement: Part of the team improving the AI hacker to make it more dangerous and creative.
Collaboration: Work closely with AI and engineering teams to continuously improve agent capabilities and ensure research findings are integrated into the product.

Were looking for a Technical Support Engineer to support customers through technical POCs, onboarding, and ongoing use of our autonomous security platform. Based in Israel and working closely with R&D and DevOps, youll provide real-time support to North American customers. This is a hands-on role for a cybersecurity technical expert comfortable troubleshooting and resolving issues directly with customer teams.
Responsibilites
Serve as the primary technical point of contact during customer POCs - supporting deployment, configuration, and troubleshooting so prospects see value fast.
Own technical onboarding for new clients, guiding them through setup, integrations, and initial configuration of the platform.
Provide ongoing technical support to live customers, diagnosing and resolving issues across the product and its integrations.
Run live technical calls with customers over Zoom, Meet, or Teams, and support them asynchronously via email, Slack, and our ticketing system.
Triage, reproduce, and document bugs and feature requests, and escalate to R&D and DevOps with the technical context they need to act quickly.
Work closely with Israel-based R&D and DevOps teams as the connective layer between customer environments and the engineering roadmap.
Build and maintain internal and customer-facing documentation, runbooks, and troubleshooting guides.
Track support activity and flag trends or recurring issues that point to product or process improvements.
Contribute to the development of our global support framework and team, while establishing operational procedures and evaluating technical tooling.

We're looking for someone with great analytical skills, preferably with a background as a data analyst or technical implementation IC - someone who's enthusiastic about both doing complicated technical implementation and solving problems with customers.

Own multiple technical implementation flows:

1. Analyze customer catalogs (10-100k of rows with multiple properties and interdependencies) and model them into our platform.

2. Implement and troubleshoot customer rules that feed our AI 3D design.

3. Help customers with last mile solutions to get our data into their required formats.

4. Own and improve internally built AI tools for the above workflows.

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We are a young, dynamic hi-tech company seeking a passionate, resilient, and proactive Technical Support Engineer to join our growing team.
In this role, you will become an expert in the inner workings of our platform and take responsibility for Tier-1 support, cross-team investigations, and customer success enablement. You will work closely with Product, Engineering, and Business teams to ensure a smooth client experience, providing guidance, issue resolution, proactive support, and intiatiives to improve the team's performance
This is a demanding and fast-paced role ideal for someone who thrives under pressure, has deep empathy for users, and is excited about solving problems and helping others succeed.
Responsibilities:
Serve as the first point of contact for Tier-1 technical support, handling and triaging issues through Zendesk and collaborating as needed across departments.
Investigate root causes, debug issues, and coordinate escalations with engineering and product teams.
Guide customers through platform features, API integrations, and SFTP connections.
Help define and improve internal workflows by creating documentation, process diagrams, and training materials.
Reproduce and debug customer-reported problems, escalating appropriately and following up for timely resolution.
Conduct deep investigations into technical issues and ensure accurate handoff to relevant teams.
Provide product education and support to clients, helping them understand platform functionality.
Being on call for urgent issues as part of a regular rotation.

Location: Tel-Aviv Type: Full-time Seniority: 6+ years experience.

This is your opportunity to join a top-notch tech solution and have true ownership over something with a massive impact.

You Will
Design, build, and maintain core backend infrastructures.
Architect scalable, modern, cloud-native flows.
Own backend systems from design to deployment and monitoring.
Help shape backend standards and long-term technical decisions.
Collaborate in fast-paced, daily brainstorming with a technical founding team.
Our Tech stack spans multi-language backend, cutting-edge infrastructure, and cloud-native systems - all built by a fast-moving team that runs lean and thinks sharp.

A growing B2B SaaS company is looking for an experienced Head of Data Science to lead its Data Science function and drive the next generation of AI and machine learning capabilities.
This is a strategic leadership role combining people management, hands-on problem-solving, cross-functional collaboration, and ownership of data-driven innovation across the organization.
Responsibilities
Lead and mentor a global team of Data Scientists
Define and execute the company's Data Science strategy
Drive the development of advanced machine learning, optimization, and forecasting solutions
Partner closely with Product, Engineering, Customer Success, and executive leadership
Translate complex business challenges into scalable analytical solutions
Support customer-facing initiatives and strategic engagements when needed
Establish best practices for experimentation, model evaluation, and performance measurement
Act as a key stakeholder in shaping the company's AI vision and roadmap.

We're looking for a Data Engineer to own our data architecture end-to-end. You'll design, build, and scale the pipelines that power every pricing decision we make - from raw ingestion through our data lake to the analytics and BI layers our customers rely on. This is a hands-on leadership role: you'll set technical direction, drive architectural decisions, and mentor a team of data engineers, while still writing code and owning delivery.
What You'll Do:
Architect and build large-scale batch and streaming ETL/ELT pipelines
Own data lake design, table modeling, and partitioning strategy across billion-row datasets
Drive query performance and cloud cost optimization across AWS and GCP
Establish data quality, observability, and reliability standards - freshness, correctness, and SLAs
Partner with backend, product, and data science teams to expose data through internal and customer-facing APIs
Our Stack
Spark / EMR Airflow BigQuery PostgreSQL & Aurora Kafka RabbitMQ Elasticsearch Go Python AWS GCP Kubernetes Terraform.

We are looking for a Senior Customer Success Manager who combines business understanding, analytical thinking, and technical aptitude to help global customers achieve measurable results with us.
You will own customer relationships throughout the post-sales lifecycle, from adoption and ongoing optimization to renewal and expansion. You will work with pricing teams, technical stakeholders, and senior management to translate business goals into practical platform configurations, analyze results, and lead discussions that turn insights into decisions.
Success in this role requires confidence working with both people and numbers, curiosity about how things work, and the independence to take ownership of complex initiatives and drive them to completion.
Key Responsibilities:
Own relationships with global B2B customers, serving as their trusted advisor and primary point of contact.
Understand each customers business and pricing objectives, define measurable success goals, and drive clear action plans.
Lead business reviews, pricing workshops, and executive discussions, translating data and complex topics into clear recommendations and decisions.
Configure pricing strategies, business rules, and workflows, review customer data and recommendations, and investigate unexpected results.
Analyze pricing and business performance, including revenue, margin, and sell-through, to identify opportunities and demonstrate customer value.
Independently lead customer initiatives from definition to completion, coordinating internal teams, resolving blockers, and keeping stakeholders informed.
Drive adoption, identify account risks, and manage renewals and expansion opportunities, including scope discussions, proposals, and negotiations.
Maintain accurate and up-to-date account information in HubSpot and ClickUp, including customer health, commercial opportunities, key decisions, commitments, owners, and timelines.

Required Lead Backend Engineer
About the Role:
As a Senior Backend Engineer on the Exchange Engine team, you will be a driving force behind the core systems of our massive mobile advertising platform. You will tackle complex architectural challenges where every millisecond counts, building real-time, highly concurrent systems that process millions of requests per minute. In this position, your impact extends beyond feature implementation; you will take charge of major initiatives, architect core systems, and raise the bar for engineering excellence across the entire team.
Key Responsibilities:
Architectural Design & Execution: Lead the end-to-end design, development, and delivery of complex, scalable, and highly available backend services for our real-time ad exchange. Architect systems with a focus on long-term maintainability, ensuring that large-scale changes and migrations are predictable and low-risk.
Performance Optimization: Profile, tune, and optimize system performance to ensure ultra-low latency and high throughput under massive concurrent loads.
Technical Mentorship: Act as a technical multiplier by mentoring junior and mid-level engineers, conducting rigorous code reviews, shaping technical standards, and promoting software engineering best practices.
Cross-Functional Leadership: Collaborate directly with Product Managers, Data Scientists, and other engineering squads to translate complex business requirements into robust technical solutions and to understand the revenue journey, ensuring technical decisions directly support market competitiveness and platform growth.
Production Excellence: Own the lifecycle of your services in production. Implement advanced monitoring, alerting, and observability to troubleshoot and resolve deep-system production incidents.
Infrastructure Collaboration: Work closely with DevOps to optimize our deployment pipelines and cloud infrastructure (Kubernetes, GCP).
AI-Driven Engineering: Leverage modern AI coding assistants and agentic tools to accelerate development velocity, automate routine tasks, and free up cognitive load for complex architectural challenges.

Required Senior Software Engineer (Full Stack)
The Role:
We run on small, autonomous pods that own an outcome and a roadmap end to end. We hire engineers, not language specialists: we care that you can reason about systems, pick the right tool for the problem, and ship reliable software across the stack.
As a Senior Full Stack Engineer, you'll build the product surfaces that bring our marketplace together - campaign management and creation, unified dashboards and reporting, audience and asset tooling, and the APIs that connect demand to supply. You'll work across front-end, back-end, and data, contributing to the unified product architecture at the heart of our FY27 roadmap. The underlying platform requires heavy back-end engineering, low-latency optimization, and algorithmic problem-solving to manage massive throughput and real-time marketplace dynamics.
About the Senior Full Stack Engineer Role:
Design and build full-stack features: from responsive web front-ends to back-end services and APIs - that power campaign management, reporting, and marketplace optimization
Choose the right language and tools for each problem (we run a polyglot stack), and keep the front end lightweight by pushing complex computational logic, data modeling, and heavy algorithmic weight into robust, scalable back-end services
Build and consume well-designed APIs that integrate DT products into a unified architecture rather than isolated silos
Own your services in production: testing, observability, performance, and on-call, treating quality as a whole-team responsibility
Collaborate directly with product leads and stakeholders, contributing to scoping, estimation, and technical decisions within your pod
Mentor teammates and raise engineering standards through code review, automation, and pragmatic architecture