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We're looking for a Customer Success Manager for our Sales Intelligence clients with a robust background in analytical skills to deliver value in a consultative manner to our clients. The CSM will serve as a strategic partner, assisting our customers in unleashing the full potential of the company platform to optimize their sales strategies.
This role will report to the Team Manager, Sales Intelligence Customer Success, TLV.
Why is this role so important at our company?
The CSM's ability to create relationships with the clients and help them extract real business value, using the company platform, is essential to keeping clients engaged with our company for years.
The CSM is on the front line, serving as a trusted advisor who brings our platform and data to life for the client
The CSM drives user engagement and adoption of our platform and helps identify growth opportunities by addressing the client's pain points
So, what will you be doing all day?
Your role as part of the Customer Success team means your daily responsibilities may include:
Lead, manage, and expand long-term customer relationships
Focus on understanding the clients specific sales strategies, challenges, and objectives to drive positive business outcomes
Share best practices and insights on lead generation, routing, and qualification processes with customers
Deliver ongoing training and support, empowering customers to adopt a consultative selling approach to increase sales efficiency
Managing product implementation and monitoring usage to ensure user engagement throughout the customer lifecycle
Develop and execute strategic customer success plans, deliver business reviews, and drive overall customer satisfaction
Identify and mitigate churn risks, implementing proactive measures to retain customers and enhance their experience
Collaborate with internal teams and stakeholders (Sales, Product, Legal, Billing, etc.) to align on commercial goals and product-related updates.

We're looking for a true data enthusiast: someone passionate about translating business needs into data solutions, building strong relationships, shaping methodologies and processes, and owning complex data initiatives from end to end.
This role will report to the VP of Product Management, Data.
What Youll Do
Data Product Ownership
Own the vision, roadmap, and delivery of critical datasets that underpin platform functionality, decisioning systems, and customer-facing features.
Lead modularization of data structures to enable scalability, easier ownership distribution, and data quality improvements.
Introduce metrics for quality (completeness, coverage, freshness, accuracy) and define validation, logging, and governance frameworks.
Cross-Functional Leadership
Serve as the product voice for data across R&D, aligning platform engineers, analysts, scientists, and business teams around a common strategy.
Bridge between domain-specific product teams and platform data infrastructure, translating business needs into scalable, reusable data assets.
Define data SLAs, fallback mechanisms, enrichment strategies, and quality assurance mechanisms in partnership with data consumers.
Strategic Impact
Prioritize and plan data initiatives that support new verticals, geographies, product features, and business models.
Spearhead productization of internal datasets into revenue-generating assets for both direct sales and platform distribution.
Deeply understand the customers evolving needs and enable the data to capture them accurately and scalably.
Execution & Optimization
Write clear product specs that include technical definitions, mapping rules, edge case handling, and downstream consumption logic.
Work hands-on with Databricks, Spark, SQL, and Python to analyze datasets, test logic, or collaborate on experiments.
Identify data anomalies, misclassifications, and inconsistencies, and lead efforts to resolve them in systematic and productized ways.
Design workflows for historical tracking and versioning of datasets.

We are looking for a talented and dedicated ML & Big Data Analyst who will be a part of the Core Data group.
As part of this role, you will help us process and streamline rich and complicated datasets. Will explore and validate new data sources. Be part of the data science and data engineering force creating new features for our solution.
What does the day-to-day of a ML & Big Data Analyst at our company look like:
Apply your expertise in quantitative analysis and data mining to turn data into insights.
Conduct research and develop tools that will ensure the quality of our companys data and algorithms.
Utilize your deep understanding of our companys data in order to evaluate and improve novel algorithms produced by the data scientists in your team.
Partner with Big Data Engineers to establish an infrastructure to scale solutions.

Were looking for an Experienced Full Stack Developer to design, code, and manage our companys large-scale and highly available services, using cutting-edge technologies and modern design practices.
This position is within the Shopper Intelligence team, the group behind our companys eCommerce product. Operating as a startup within our company, the team combines the energy, agility, and innovation of an early-stage company with the resources and reach of a global leader. Youll be joining a highly dynamic environment where ideas move quickly from concept to product, and your work will have a direct impact on shaping one of our companys fastest-growing solutions.This role reports directly to the Team Manager, R&D.
Why is this role so important at our company?
We are a company that is driven by innovation, which means that we are constantly building and developing new features and products to meet customers needs.
As a full stack developer, you will have the opportunity to work with the most cutting edge technologies, to solve complex challenges, and create high quality and scalable code. Your work will have a direct impact on customer satisfaction and our business objectives.
So, what will you be doing all day?
Your role as part of the R&D team means your daily responsibilities may include:
Designing, coding and managing large scale, highly available services using cutting-edge Client/Server technologies (NodeJS, React, TypeScript, JavaScript, Redis, Docker, etc.)
Design, develop, and maintain server-side logic using TypeScript frameworks.
Building scaled-data pipelines, loading data into serving layers. Using ETL frameworks like Databricks and Airflow.
Leading decision-making & design of APIs, mechanisms and abstractions.
Working in a BigData environment, using Firebolt as data warehouse.
Building new features and directly impacting the future of our product from UI to DB
Writing (a lot of) high-quality, functional code backend and frontend
Performing code reviews, evaluating implementations, and provide feedback.

What Youll Do:
Youll be part of the group responsible for our companys main products. You will impact the work of developers in the group by designing, building and maintaining the core infrastructure of our solution and leading the research and development of new technologies as well as maintaining code standards and practices.
What does the day to day of Infrastructure Engineer at our company look like:
You will be working on our companys core B2B platform that serves tens of thousands of customers, serving hundreds of terabytes in production. Our backend engineers are responsible for the entire data lifecycle - from our endless datatlakes, through choosing the right serving methods and databases, all the way to our api services.
Your role will include:
Design and implement scalable backend services and libraries that are reusable and maintainable, serving as the foundation for various applications across the company.
Build and maintain tools that streamline development workflows, enabling product teams to focus on delivering business value.
Define and promote best practices for code quality, performance, and reliability, ensuring healthy production environments and rapid development cycles.
Lead the adoption and integration of AI tools to assist in code generation, testing, documentation, and debugging, thereby accelerating development processes.
Perform proof-of-concepts (POCs) on emerging technologies, including AI agents and platforms, to assess their applicability and benefits to our development ecosystem.
Drive cross-team technical projects aimed at improving infrastructure scalability, reliability, and developer experience.
Analyze and resolve complex production issues, ensuring minimal downtime and optimal performance.
Contribute to the evolution of our system architecture, ensuring it supports rapid development and scaling needs.

Were looking for a sharp and driven Data Analyst 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 Data Analyst Customer Facing (Data Labs) at our company 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 which will help answer client's business. questions by using our companys raw data sets and algorithms.
Partner with Engineering teams to establish an infrastructure to scale solutions.
Partner with Advisory Services team of Consultants to answer strategic business questions and deliver custom data products seamlessly.

As an AI Engineer at our company, you will be a key player in building our new AI platform, AI Studio. This platform aims to provide users with instant answers to complex market research questions, generate world-class reports, and create live, interactive, and powerful dashboards. Our goal is to reduce the complexity and time-to-insight for our users, helping them streamline their market tasks and achieve automation that drives real value.
Responsibilities:
Design and develop LLM-based intelligent agents that can handle complex market research queries.
Utilize LangGraph and other frameworks to create state of the art AI agents that integrate various tools and data sources.
Implement integrations that allow agents to take automated actions on behalf of users, streamlining workflows and reducing overhead.
Collaborate with product, data, and UX teams to ensure that AI solutions are aligned with user needs and business goals.
Continuously evaluate and improve the performance of AI models to ensure high-quality and data-driven results.

Were looking for a Salesforce CPQ Solutions Engineer to lead the design and delivery of scalable, efficient CPQ systems that streamline quoting, pricing, and sales processes. If youre passionate about translating complex pricing models into powerful automation, and enjoy collaborating with cross-functional teamsthis is the role for you.
The ideal candidate combines a solid understanding of business pricing strategies with hands-on experience in building scalable, maintainable CPQ systems that enhance sales efficiency and ensure quoting accuracy.
This role is both strategic and technical, requiring close collaboration with cross-functional teams including sales, finance, and operations.
Key Responsibilities
End-to-End CPQ Implementation
Lead the design and build of Salesforce CPQ implementations from requirements gathering through deployment and support.
Translate complex business pricing structures into automated CPQ configurations.
Own the technical setup of product catalogs, price rules, discount logic, approval processes, and quote templates.
Pricing Strategy & Business Modeling
Work with business stakeholders to understand pricing models: subscription, usage-based, tiered, volume, and hybrid models.
Support bundling strategies, SKU rationalization, and guided selling logic.
Build rules that reflect approval thresholds, partner discounts, and contract conditions.
Advanced CPQ Configuration
Implement:
Product, Price, Constraint, and Lookup Rules
Dynamic bundles, guided selling flows, configuration attributes
Custom quote templates, document generation, and approval automation
Ensure modular, scalable, and well-documented configuration that aligns with long-term growth.
Cross-Functional Collaboration
Serve as the subject matter expert for CPQ across departments.
Partner with Sales Ops, RevOps, Finance and Information Systems to align CPQ systems with the companys go-to-market strategy.
Provide enablement materials and training for end-users and administrators.
Project & Stakeholder Management
Drive project delivery: scope, timeline, risk management, and deployment.
Communicate clearly with both technical and non-technical audiences.
Maintain a service-oriented mindset that supports adoption and business satisfaction.

We are looking for a Data Engineer to join our team and help advance our Apps solution. Our product is designed to provide detailed and accurate insights into Apps Analytics, such as traffic estimation, revenue analysis, and app characterization. The role involves constructing and maintaining scalable data pipelines, developing and integrating machine learning models, and ensuring data integrity and efficiency. You will work closely with a diverse team of scientists, engineers, analysts, and collaborate with business and product stakeholders.
Key Responsibilities:
Develop and implement complex, innovative big data ML algorithms for new features, working in collaboration with data scientists and analysts.
Optimize and maintain end-to-end data pipelines using big data technologies to ensure efficiency and performance.
Monitor data pipelines to ensure data integrity and promptly troubleshoot any issues that arise.

We are seeking a highly motivated and experienced IT Operations Team Leader to manage and oversee all internal IT support operations across our global organization. This pivotal role requires someone with strong leadership capabilities, technical expertise, and a passion for driving operational excellence in a fast-paced, cloud-native software environment.
You will lead a distributed team of IT Support Engineers across the US, EMEA, and APAC regions, ensuring the smooth and secure functioning of our internal IT systems and user support services. You will be responsible for critical platforms and processes that enable our employees to work efficiently and securely.
Key Responsibilities
Lead and mentor a global team of IT Support Engineers across multiple time zones.
Manage daily operations, workload allocation, ticket prioritization, and team performance.
Define and enforce SLAs and KPIs for support services.
Oversee the administration and optimization of key platforms including: Google Workspace, Okta (SSO and identity lifecycle management), Office 365, Mobile Device Management platforms
Ensure all endpoints (Mac and Windows) are properly managed, secured, and compliant with policies.
Supervise the provisioning and deprovisioning of hardware and software for new hires, transfers, and terminations.
Own and continuously improve onboarding and offboarding workflows, ensuring seamless and secure transitions.
Partner with Employee Services and Security teams on cross-functional initiatives, including access reviews, compliance audits, and automation.
Identify opportunities for automation and efficiency gains in IT support operations.
Drive global standardization of IT tools, processes, and documentation.
Lead or participate in cross-functional projects related to internal systems, collaboration tools, and infrastructure.

A day-to-day role as a Team Manager at our company includes:
Managing a multidisciplinary team of data engineers, data scientists, and data analysts.
Leading the development of advanced and creative solutions for complex technical challenges in areas like big data and machine learning.
Collaborating closely with data extraction, platform, and product teams.
Communicating with business stakeholders and gathering feedback from customers.
Hiring new team members and developing the groups structure.
Playing a crucial role in shaping product strategy within a startup-like environment.
Day-to-day, the team you will lead will:
Develop statistical and machine learning algorithms on large-scale data to estimate metrics, create features, and deliver insights.
Own end-to-end data processes and pipelines, from research and proof of concept to production.
Collaborate with product and R&D teams to plan and deliver best-in-class digital insights.
Design, validate, and monitor ongoing processes to ensure quality and reliability.
Identify, analyze, and monitor new raw data sources as needed.

What Youll Do:
Youll be part of the group responsible for our companys main products. You will impact the work of developers in the group by designing, building and maintaining the core infrastructure of our solution and leading the research and development of new technologies as well as maintaining code standards and practices.
What does the day to day of Infrastructure Engineer at our company look like:
You will be working on our companys core B2B platform that serves tens of thousands of customers, serving hundreds of terabytes in production. Our backend engineers are responsible for the entire data lifecycle - from our endless datatlakes, through choosing the right serving methods and databases, all the way to our api services.
Your role will include:
Design and implement scalable backend services and libraries that are reusable and maintainable, serving as the foundation for various applications across the company.
Build and maintain tools that streamline development workflows, enabling product teams to focus on delivering business value.
Define and promote best practices for code quality, performance, and reliability, ensuring healthy production environments and rapid development cycles.
Lead the adoption and integration of AI tools to assist in code generation, testing, documentation, and debugging, thereby accelerating development processes.
Perform proof-of-concepts (POCs) on emerging technologies, including AI agents and platforms, to assess their applicability and benefits to our development ecosystem.
Drive cross-team technical projects aimed at improving infrastructure scalability, reliability, and developer experience.
Analyze and resolve complex production issues, ensuring minimal downtime and optimal performance.
Contribute to the evolution of our system architecture, ensuring it supports rapid development and scaling needs.

We are looking for an Android Developer.
What does the day to day of a Mobile Developer at our company look like:
Design and write (a lot of) high-quality, functional code of B2C apps with millions of paying and non-paying users.
Tackle challenges and find creative and innovative ways to solve them.
Determine feasibility & take part in decision-making by performing risk management and evaluating trade-offs.
Contribute to your team development velocity and quality confidence.
Improve your skills, learn from and mentor top-notch engineers and enrich other team members.
Perform code reviews, evaluate implementations, and provide feedback.
Have lots of fun!

We are seeking a skilled Data/ Backend Engineer to design and implement complex, high-scale systems that retrieve, process, and analyze data from the digital world. This role involves developing and maintaining backend infrastructure, creating robust data pipelines, and ensuring the seamless operation of data-driven products and services.
Key Responsibilities:
- Design and build high-scale systems and services to support data infrastructure and production systems.
- Develop and maintain data processing pipelines using technologies such as PySpark, Hadoop, and Databricks.
- Implement dockerized high-performance microservices and manage their deployment.
- Monitor and debug backend systems and data pipelines to identify and resolve bottlenecks and failures.
- Work collaboratively with data scientists, analysts, and other engineers to develop and maintain data-driven solutions.
- Ensure data is ingested correctly from various sources and is processed efficiently.

Were looking for a Data Scientist to join our Data Labs department, which specializes in professional services for our super premium customers.
This role will report to our Datalabs Team Manager in the, R&D.
Why is this role so important at our company?
we are a data-focused company, and our unique AI and machine learning capabilities are the center of our business.
As part of this role, you will create data models that help analyze the petabytes of data we receive from various sources, and research and develop new features and capabilities for our product solutions
As a data scientist in the Datalabs team, you will work on the very core of the company. Part of your role will be to turn raw data into usable metrics and develop new models and statistical algorithms to support out-of-the box requests from customers who want custom digital insights. The Datalabs departments customer centric and business-oriented nature also means you will be supporting a team of data analysts and consultants who interact directly with customers. Together with them, you will translate the voice of these customers into best-in-class digital insights.
So, what will you be doing all day?
Your role as part of the R&D department, and as part of the Datalabs team means your daily responsibilities may include:
Working on versatile use cases within a dynamic, fast paced production environment
Strategic thinking and problem solving, with a strong business sense
Analyzing data from various sources, and turning it into usable input
Understanding various use cases from different customers, and creating models that can translate these cases into meaningful insights
Initiating newly defined tasks from exploration to proof of concept
Owning the finalization of defined tasks (from POC to deployment in production)
Collaborating with data engineers to make sure we reach the desired production results
Owning the ongoing validation process for existing metrics
Collaborating and brainstorming best practices with other teams within the R&D department
Deploying machine-learning models into production for an ongoing use.