דרושים » תוכנה » French Data Annotator and Analyst

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 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.

Required Data Scientist
About the Role
The Data Science department plays a pivotal role in our company, generating value to us by developing algorithms and analytical production-grade solutions. We leverage advanced techniques and algorithms to provide maximum value from data in all shapes and sizes (such as classification models, NLP, anomaly detection, graph theory, deep learning, and more). As a Data Scientist, you will assume the classic data-science role of an end-to-end project development and implementation practitioner. Being part of the team requires a mix of hard quantitative and analytical skills, solid background in statistical modeling and machine learning, a technical data-savvy nature, along with a passion for problem-solving and a desire to drive data-driven decision-making.
What You'll Be Doing
Data Exploration and Preprocessing: Collect, clean, and transform large, complex data sets from various sources to ensure data quality and integrity for analysis
Statistical Analysis and Modeling: Apply statistical methods and mathematical models to identify patterns, trends, and relationships in data sets, and develop predictive models
Machine Learning: Develop and implement machine learning algorithms, such as classification, regression, clustering, and deep learning, to solve business problems and improve processes
Feature Engineering: Extract relevant features from structured and unstructured data sources, and design and engineer new features to enhance model performance
Model Development and Evaluation: Build, train, and optimize machine learning models using state-of-the-art techniques, and evaluate model performance using appropriate metrics
Data Visualization: Present complex analysis results in a clear and concise manner using data visualization techniques, and communicate insights to stakeholders effectively
Collaborative Problem-Solving: Collaborate with cross-functional teams, including product managers, data engineers, software developers, and business stakeholders to identify data-driven solutions and implement them in production environments
Research and Innovation: Stay up to date with the latest advancements in data science, machine learning, and related fields, and proactively explore new approaches to enhance the company's analytical capabilities.

Were looking for a Data scientist Expert to join us and spread the power of our company. As a Data Scientist you will be responsible for driving research and development of autonomous AI agents and LLM-powered systems at our company. You will work closely with cross-functional teams to explore, innovate, and implement AI-driven solutions to tackle emerging threats, examine cloud security features, and enhance the companys security posture.
WHAT YOULL DO
Lead applied research on AI agents and LLM-driven features in the company platform - from autonomous threat investigation agents to AI-powered security operations workflows
Cover a range of features - from leveraging LLMs to enhance customer investigation experience to novel usage of AI for cloud security
Collaborate with engineering teams to design, build, and maintain production pipelines
Work closely with the Security Research and Product teams to define research goals
Conduct experiments and evaluate the performance of AI models, algorithms, and techniques using real-world datasets and simulated environments
Stay abreast of cutting-edge AI methodologies, frameworks, and tools and apply them to improve security solutions' accuracy, efficiency, and scalability.

We are seeking an experienced and visionary Data Scientist to join our dynamic technology organization. The successful candidate will be a part of a team of talented data scientists, driving innovation and delivering business value through advanced machine learning techniques and Generative AI solutions. This role requires a strategic thinker with hands-on expertise in both traditional and cutting-edge data science methodologies, and a passion for continuous learning and development.
Responsibilities:
Gradient boosting techniques (e.g., XGBoost, LightGBM, CatBoost) are used to enhance predictive accuracy and model robustness.
Drive the exploration and integration of Generative AI applications, including Large Language Models (LLMs), to create innovative solutions for our products and services.
Collaborate with cross-functional teams (engineering, product, business) to translate business requirements into actionable data science projects.
Establish best practices for model development, validation, deployment, and monitoring in production environments.
Promote a data-driven culture, encouraging experimentation, sharing of knowledge, and adoption of state-of-the-art technologies.
Communicate project progress, insights, and results to stakeholders at all levels of the organization. Design, implement, and optimize classic machine learning models to solve complex business problems.

We are looking for a Senior Data Products Manager to lead the strategy and evolution of our external data products, with a strong focus on customer needs and scalable, high-impact data solutions.
In this role, you will work directly with customers and internal stakeholders to understand how our data catalog is used across different use cases. Youll translate customer insights, usage patterns, and commercial input into a clear product vision and prioritized roadmap aligned with company objectives.
You will work closely with customer-facing data scientists and internal delivery teams to turn customer needs into production-ready data products. This includes collaborating with Partnerships to evaluate external data providers and defining requirements that guide the transformation of raw data into reliable, high-quality signals. You will also engage with the data pipeline itself, where different models are used to turn raw and unclassified data into coherent, scalable data products.
Responsibilities:
Own the strategy, vision, and roadmap for Exploriums external data products, guiding a delivery team of data developers and a team lead.
Lead customer discovery and translate insights into scalable product initiatives, requirements, and clear delivery plans.
Drive prioritization across competing needs, balancing customer value, business impact, feasibility, and time-to-market.
Lead the end-to-end data product lifecycle: discovery, definition, delivery, launch, adoption, and continuous improvement.
Collaborate cross-functionally with Data Science, Engineering, Sales, CS, and Partnerships to validate use cases and define measurable product success.
Write clear product specs and actionable tickets that guide the transformation of third-party data into production-grade data products.
Continuously improve existing products to expand coverage, improve accuracy, and unlock new customer use cases.
Define and track success metrics such as adoption, customer impact, accuracy, coverage, and performance.

We are looking for an experienced Data Scientist who can leverage and develop innovative machine learning, NLP, and generative AI technologies, for solving problems within a wide scope.
As a part of our Data Science group, you will work on highly complicated challenges, from research to production, and help shape our algorithms and AI platform. You will work with Developers, Analysts, Product Managers, and business owners on growth opportunities and new ideas.
You should have a strong background and experience in the machine learning pipeline through business understanding, research, data exploration, feature engineering, model building, performance evaluation, testing, production-level code and deployment, model monitoring, and maintenance.
What am I going to do?
Take leading roles in projects such as search engine ranking, promoted ads in our companys search results, recommendations, users segmentation and personalization, online bidding optimization, text analysis, real-time predictions, live streaming data handling, exploration-exploitation problems, etc.
Work closely with various departments in the company to provide advanced Data Science solutions end to end.
Write and own production models and code.
Independent research and innovation in new content and technological domains.
Lead and advise other team members.
Continuously produce new initiatives and improvement ideas.
Act as a leader of our companys AI platform. Develop models and framework solutions for the group.

Applied Data Scientist
Tel Aviv, Israel (Hybrid On-site)
Full-Time
We are the trust layer backbone for the Generative AI revolution, building the critical testing infrastructure needed to enable the next generation of AI: Agentic Systems. We provide an end-to-end platform that goes beyond simple metrics to evaluate complex, multi-step LLM workflows. Our technology employs a swarm of specialized evaluation agents to validate complex AI workflows and isolate the root cause of errors. We empower organizations to solve the black box problem, ensuring their agents are reliable, safe, and hallucination-free from the first prototype to high-scale production.
About the Role
As an Applied Data Scientist, you will research, design, and implement complex algorithms that assess and monitor AI systems, including cutting-edge LLM applications. You will work in a high-paced environment where impact is key. You will collaborate closely with our engineering and product teams to push the boundaries of what automated AI evaluation can achieve, ensuring our users get the most reliable and actionable insights possible.

we are looking for a Manager, Data Science & Research.
What you will do
You will lead a team of experienced Data Scientists while remaining deeply involved in the technical work.
This is a hands-on leadership role (~70% hands-on) combining direct modeling work with ownership of team direction and execution.
You will work on core systems that operate at a massive scale, where:
Data is abundant, but labels are scarce and expensive
problems are long-tail and ambiguous
Systems must meet strict latency and cost constraints (pre-bid)
Your responsibilities include:
Lead development of content classification systems across social platforms (Meta, TikTok, YouTube), web, and apps
Design and build models across computer vision, NLP, and multimodal pipelines
Own the full lifecycle: data selection -> labeling strategy -> training -> evaluation -> deployment
Develop strategies for efficient data curation and labeling (active learning, auto-labeling, sampling under scale)
Improve model quality (precision/recall) while balancing cost, latency, and scale
Drive automation systems (auto-labeling, auto-curation, retraining loops)
Apply modern AI approaches (LLMs, embeddings, foundation models) to real production problems
Lead and mentor a team of senior Data Scientists, setting technical direction and pushing execution forward
Work closely with ML Engineering, Product, and Policy to translate ambiguous requirements into scalable systems

Join our team as a Geo Analyst and play a key role in producing the underground utility maps that sit at the heart of our product. In this entry-level position, youll work hands-on with diverse geospatial datasets and real project outputs, developing a deep understanding of how raw information becomes accurate, high-impact mapping for our customers.

Responsibilities

Process, extract, and analyze spatial data from multiple sources, including aerial imagery, remote sensing, engineering plans, surveys, and web-based datasets.
Deliver customer projects on time and at high quality, working in a fast-paced, deadline-driven environment.
Interpret and classify underground utilities and construction activities using geospatial tools and digital imagery.Work with GIS tools (mainly QGIS) to review, validate, and edit geospatial data.
Perform quality assurance (QA) in collaboration with external and internal experts.