דרושים » תוכנה » AI & LLM Data Analyst (Customer-Facing)

Were looking for a Data Analyst to join the Data for AI team. This is a hands-on, customer-facing role focused on working with leading AI companies to turn real-world data into inputs that support model development and evaluation.
Youll collaborate closely with external AI teams and internal engineering and product partners to deliver data-driven solutions for specific AI use cases. The work is fast-paced, technical, and often open-ended, requiring comfort with large datasets, ambiguous requirements, and end-to-end ownership.
What does the day-to-day looks like:
Own end-to-end delivery of data solutions for AI use cases, from understanding model and product requirements to analysis, implementation, quality, and automation
Work hands-on with large, raw datasets to create high-quality data inputs that support model training, evaluation, and iteration
Apply strong quantitative analysis and data exploration skills to assess coverage, quality, and behavior of data used in AI systems
Build scripts, analyses, and reusable components in Python and SQL to support scalable and repeatable workflows
Collaborate closely with Engineering to ensure solutions are reliable, scalable, and production-ready
Partner directly with external AI teams and internal stakeholders to translate open-ended questions into concrete data outputs

We are looking for a Data Analyst with strong Python and engineering capabilities to join our Data team.

This is not a traditional analytics role - it combines data analysis with hands-on development. You will work extensively with Python as part of your day-to-day work, building scalable data processes, evaluation frameworks, and classification logic that directly impacts our product.

Our team works on large-scale data systems, leveraging ML capabilities such as NER and LLMs, alongside robust engineering and analytics to deliver insights across millions of files and tables daily.


Responsibilities
Design and implement data classification logic to expand coverage of sensitive data types, owning the process end-to-end - from research and analysis to production deployment
Develop Python-based workflows and tools for data processing, evaluation, and automation
Build and maintain data pipelines and monitoring systems to track product performance and data quality
Create automated frameworks to evaluate and benchmark model performance
Collaborate closely with R&D and take part in discussions around AI/ML solutions and product direction

Were looking for an Applied Data Scientist to join one of our product squads. Youll design, build, and deploy data-driven solutions that combine machine learning, statistical methods, and SQL/rules-based decision logic to power autonomous supply chain intelligence platform. Youll work closely with data science, engineering, product, and supply chain experts and own solutions end-to-end-from problem definition to production monitoring and iteration.
Responsibilities:
Deliver data science solutions end-to-end within a product squad: problem framing → data prep/labeling → modeling → deployment support → monitoring → iteration
Build, train, and improve ML models for supply chain use cases (e.g., inventory risk prediction, demand anomalies, root-cause analysis)
Define success metrics and evaluation plans with support from senior DS/PM; run error analysis and document learnings
Work with stakeholders to create and maintain ground truth (label definitions, labeling workflows, QA checks, feedback loops)
Implement hybrid decision logic by combining ML outputs with statistical methods and SQL/rules-based logic for robustness and explainability
Analyze large, multi-source operational datasets to identify trends, anomalies, and drivers of performance
Collaborate with software engineers to productionize solutions (batch and/or real-time), including testing, logging, and basic monitoring
Monitor deployed models/rules, investigate performance issues (data quality, drift, edge cases), and iterate based on outcomes
Contribute to team practices: reproducible notebooks/code, documentation, and experiment tracking

Were looking for a Senior Data Engineer to own high-impact data products from architecture through production deployment, monitoring, and continuous improvement. This isnt a pure infrastructure role - youll combine strong engineering with product thinking, operational excellence, and awareness of data quality, cost, and business impact.
You will design, implement, test, deploy, and maintain production-grade data products - pipelines, transformation layers, data quality and reliability systems - using tools like DBT (on Spark) and Databricks. Youll apply best practices in Python and SQL to build scalable and maintainable data transformations, and leverage technologies like LLMs and GenAI to create innovative solutions for real business problems.
This role is ideal for someone who wants technical leadership responsibilities in an AI-first engineering culture - we use LLMs, GenAI, and AI-native development tools as core parts of our daily workflow.
Key Responsibilities:
Act as a technical leader within the team - raise engineering standards, drive strong architectural choices, and improve how we build
Own data products end-to-end: design, development, deployment, monitoring, and iteration
Work closely with senior leadership to translate strategic goals into scalable data solutions
Develop and maintain production ETL/ELT pipelines using DBT (on Spark) and orchestrated workflows in Databricks
Build monitoring, alerting, and testing pipelines to ensure reliability and performance in production
Evaluate and introduce new technologies - including AI-native development tools - and integrate the ones that create real impact
Collaborate with customers and external data providers - gathering requirements and making product decisions.
Mentor team members through code reviews, pairing, and knowledge sharing

We are looking for a native French speaker with a high level of proficiency in English to join our Annotation and Analysis team at the as a Data Annotator and Analyst.
In this role, you will work with large volumes of data in both French and English, annotating and analyzing datasets used to evaluate and train machine learning models, including large language models (LLMs). Your work will involve reviewing model outputs and preparing high-quality training data that supports the development and continuous improvement of AI-driven products. In addition, as part of the job, you will conduct complex analysis on the annotated data and provide insights to the other stakeholders.
This position is ideal for someone passionate about linguistics and data, and who enjoys working on detail-oriented tasks that directly impact model quality. As part of a collaborative, cross-functional team, you will work closely with Data Scientists and Product Managers to ensure that datasets are accurately labeled and annotation standards support the development of reliable machine learning systems.
Responsibilities :
Evaluate the quality of machine-translated text, with a focus on French language accuracy and fluency.
Annotate and assess AI model responses to support systematic evaluation and improvement of model performance.
Create high-quality annotated datasets used to train and evaluate LLMs and other NLP models.
Write and refine LLM prompts that support scalable human annotation workflows.
Collaborate with cross-functional teams, including Data Scientists and Product Managers, to communicate linguistic nuances and implications of French translations on model behavior and user experience.
Analyze annotated data and evaluation results to identify patterns, assess model quality, and surface insights for model improvement.

Realize your potential by joining the leading performance-driven advertising company!
our companys Strategy and Intelligence team is building an execution-first, impact-driven capability to turn data and generative AI into a core advantage for our marketing organization and beyond. We operate with startup intensity, enterprise reach, and a relentless drive for actionable insights.
As an AI Insights and Research Specialist on the Strategy and Intelligence team in our Tel Aviv Office, youll play a vital role in owning the in-depth understanding of our customer portfolio and market landscape. This role is perfect for a data-savvy analyst who thrives on uncovering best practices and is eager to build and leverage AI tools and agents to scale their impact.
Youll be a key player in a high-impact Strategy and Intelligence team with direct visibility and ownership. Were not just analyzing data the traditional way; were operationalizing AI to revolutionize how we understand our customers and market. If you like lean teams, cross-functional execution, and using cutting-edge tech to solve real business problems, this is your home.
How youll make an impact:
Lead in-depth analysis of customer activity data to uncover trends, best practices, and actionable insights for the marketing organization and broader company.
Monitor and report on key performance indicators (KPIs) regarding our customer portfolio, providing data-driven recommendations to strategy leadership.
Conduct external industry research to benchmark our company against market standards and identify emerging opportunities, including leveraging industry databases.
Own end-to-end implementation of GenAI and automation projects in order to fulfill the above tasks and more - from scoping and prompt design to testing, documentation, and rollout.
Translate business needs into structured workflows, coordinating between non-technical and technical teams.
Translate complex data into clear, strategic narratives that drive decision-making across marketing and business teams.
Execute all of the above using AI tools extensively (AI first) to increase pace and quality of outputs.

We are seeking a highly motivated and experienced Senior Product Analyst to join our team. This position is part of our Voice Group, reporting to the Data Team Lead. You'll be the analytical backbone of the team, working side-by-side with PMs and engineers to find what's working, what can be improved, and what to build next.

We are looking for someone with a relentless curiosity for both user behavior and AI/ML mechanics; someone who understands how models function and possesses a natural drive to dig into data anomalies until they make sense. Your work will directly shape how our voice agents perform, from surfacing patterns in conversation data to providing the inputs that improve our models.

Responsibilities
Analyze conversational data at scale to uncover opportunities for improving resolution rates, success rates, conversation depth, and growth.
Partner closely with Voice PMs to translate data findings into product priorities and roadmap inputs.
Provide the analytical insights and requirements that drive model improvements while collaborating with ML and engineering teams to define and own end-to-end success metrics.
Build and maintain dashboards and metrics that give the Voice group a shared, reliable view of performance.
Design and analyze experiments and A/B tests to validate hypotheses about agent behavior, conversation flows, and user outcomes.
Develop a deep understanding of our conversational data, taking full ownership of the analytical infrastructure to ensure the highest standards of data integrity and becoming the primary storyteller for your domain.
Proactively investigate data anomalies or gaps to identify root causes and propose solutions without waiting for external direction.

we are seeking an Ad Operations Analyst to drive data visibility and operational intelligence across our Supply organization. In this role, you will bridge the gap between raw programmatic logs and actionable business intelligence, helping ensure operational stability and performance across multiple integrations.
You will analyze high-volume programmatic traffic and large-scale advertising datasets, working at the intersection of operations, analytics, and product, collaborating closely with Supply Operations, Product, Data Engineering, and Business teams. This is a high-impact role where your insights will help improve operational transparency, detect issues early, and support data-driven decision-making across the organization. The team actively leverages modern AI and automation tools to enhance analytics workflows, monitoring, and data exploration.
Responsibilities:
Own and develop supply monitoring frameworks and reporting dashboards used across the Supply organization to detect and resolve revenue-impacting issues
Aggregate and analyze data from multiple internal systems and external advertising platforms to support operational monitoring and analysis
Work with large-scale datasets across multiple advertising integrations, including SSPs, exchanges, and partner platforms
Identify trends, anomalies, and operational issues while generating actionable insights
Provide insights that influence operational decisions and supply optimization strategies
Investigate data discrepancies and operational issues by combining business logic, product understanding, and large-scale data analysis
Build and maintain automated data pipelines and API-based data collection processes
Develop dashboards and data visualizations that support operational monitoring and business decision-making using modern BI and AI-enabled tools
Collaborate closely with Data Engineering to improve data infrastructure and reporting reliability
Work with Product and business teams to visualize operational data and support strategic initiatives
Design smart alerts and monitoring systems, including anomaly detection capabilities, to proactively identify operational issues
Use automation and modern AI tools to improve analytical workflows and operational efficiency

we are looking for a Reference Data Analyst (Spanish speaking).
The primary purpose of this position is to research, analyze and interpret, client queries within the Reference Data Challenge Resolutions team. The Challenge Resolution team is responsible for handling external client queries, internal stakeholder (account management, sales, product, pricing and production teams) queries and reporting and analyzing trends based off the results of these queries. The focus will be to deal with more complex queries from various external and internal sources; to update and maintain that data in various internal database and to add value through increased analysis of the queries.
Responsibilities:
Provide customer support for users of ICE products by resolving inquiries in a timely manner
Craft external facing responses for those clients that submitted customer inquiries containing a meaningful, well-thought out, well-constructed answer that includes a restatement of the challenge or question, the analysis completed to satisfy the request and where appropriate, the methodology used to determine the solution
Support our customers by resolving problems by understanding their cause, gathering the relevant information and formulating and implementing a solution with the guidance of the Manager.
Confidently participate in client calls and meetings.
Contribute to the implementation of change in services and systems, and suggest and implement improvements with the guidance of the Manager
To provide support and become an escalation point for queries in the absence of the manager.
Become a subject matter expert on more than one of our internal database/applications.
Compile team statistics and evaluate results
Liaise with other departments such as pricing, product, data collection and account management.
Identify potential new and enhanced reliable sources that can be used to gather data (i.e. a new data vendor provider)
Identify different/more effective/productive ways to use the existing sources with a view to decrease idle time/ increase speed
Provide support on continued development of the SPER query system, including suggesting enhancements and participating in testing.

Were looking for a Business Analyst - HR / People Analytics to join our fast-growing Business Analytics team and focus on building scalable people and workforce analytics capabilities across the company.
This role partners closely with People (HR), FP&A, and Data teams to deliver insights on workforce trends, hiring effectiveness, headcount planning, and people-related financial impact. The role complements existing HR analytics capabilities by focusing on cross-functional, strategic, and company-level analytics, in addition to operational HR reporting.
Youll combine strong analytical skills, understanding of people data, and business storytelling to help leadership make informed decisions about workforce planning, organizational health, and cost management.
Responsibilities
Talent & Recruitment Analytics
Analyze recruitment funnel metrics including time-to-hire, time-to-fill, conversion rates, and hiring velocity.
Support hiring plan tracking and capacity analysis in collaboration with HR and Finance.
Work closely with the HR Ops supporting Greenhouse to align data definitions and reporting logic.
Identify bottlenecks and improvement opportunities in the hiring process through data-driven analysis.
People & Workforce Analytics
Analyze workforce trends including headcount evolution, attrition, retention, internal mobility, and tenure.
Build reporting and insights around employee lifecycle metrics and organizational structure.
Partner with HR to improve data quality, definitions, and consistency across people systems.
Deliver actionable insights to People leadership and senior management on workforce health and risks.
Headcount, Cost & Financial Impact Analysis
Partner with Finance and FP&A to support headcount planning, forecasting, and scenario analysis.
Analyze the financial impact of hiring plans, attrition, and organizational changes on operating expenses.
Support workforce cost modeling, including payroll and people-related expenses.
Help align people plans with budget targets and company-level financial objectives.
Data & Analytics Operations
Use SQL and Snowflake to extract, structure, and analyze people-related data.
Build end-to-end dashboards and reports using Tableau (preferred), from data modeling to visualization.
Collaborate with Data /BI team to improve data pipelines, governance, and reporting infrastructure.
Leverage automation and AI-driven tools where applicable to improve reporting efficiency and scalability.
Cross-Functional Collaboration & Communication
Act as a trusted analytics partner to HR, Finance, and leadership stakeholders.
Translate complex data into clear insights and business stories for executive audiences.
Prepare presentations and analysis for leadership reviews, planning cycles, and strategic discussions.
Contribute to the continuous improvement of people analytics frameworks and reporting standards across the company.