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About The Position
Design, build, and maintain scalable data pipelines and infrastructure entirely within GCP
Own data solutions end-to-end, from architecture and design through to production delivery
Build and maintain custom connectors to advertising platforms including Google Ads, Meta (Facebook) Marketing API, and other ad platforms
Design and implement data warehouse structures with a deep focus on performance, scalability and usability
Continuously investigate and evaluate new GCP native tools and services, assessing their fit, building proof of concepts, and driving adoption where it makes sense
Set up and configure orchestration and transformation frameworks (such as Airflow and dbt) within the GCP environment
Collaborate closely with backend engineers to ensure data infrastructure aligns with product and system needs
Contribute to data science initiatives and bring genuine curiosity to analytical use cases
Monitor, troubleshoot, and continuously improve the reliability and performance of existing data systems
Define technical standards and best practices for the data platform
Build and maintain data dashboards and reports to surface insights for stakeholders, primarily using Looker Studio.

Required Data Scientist Team Lead
Description
About Us:
We are bootstrapped and has been profitable since day one. We built one of the most efficient programmatic acquisition engines on the planet: processing billions of ad decisions a day, generating terabytes of live behavioral data, and turning it into margins most SaaS companies would kill for.
At the core of that engine is a team of data scientists and ML engineers running tens of billions of sub-second predictions a day, deciding in milliseconds which impression is worth buying and what its worth.
Now were taking everything weve learned about how people move through the web and putting it into our most innovative consumer product yet: Ace AI, an AI-native browser already reaching millions of people, built to simplify and improve everyday online life with the help of AI.
This is a rare opportunity: a category that hasnt meaningfully changed in over a decade, and a profitable company with the data and the acquisition engine to win it on its own terms.
Come build it with us.
What Youll Do:
Mentor a team of extremely talented and success-hungry data scientists.
Initiate and manage cutting-edge projects from inception to delivery, including developing structured and automated solutions.
Lead the data strategy: be responsible for planning, prioritizing, and building the right data solutions to support business needs.
Apply your scientific knowledge and creativity to analyze large volumes of diverse data and develop algorithmic solutions and models to solve complex problems.
Identify and propose data science and algorithmic solutions for various product initiatives.
Use your excellent communication skills, both written and verbal, to explain technical concepts and analysis implications to senior leaders, and influence cross-functional teams to improve performance.
Partner with other departments (i.e. Management, R&D, Product) to support decision making.

We are looking for an experienced Senior Data Engineer to join our Data team. In this role, you will lead and strengthen our Data Team, drive innovation, and ensure the robustness of our data/analytics platforms.
A day in the life and how youll make an impact:
Design and develop high-performance Data Pipelines and ETL processes to support diverse business needs.
Work closely with Product, Business Intelligence, Sales and other teams to integrate data solutions, ensuring seamless alignment and collaboration across functions.
Continuously improve our data analytics platforms, optimizing system performance and ensuring robust, reliable data infrastructure.
Oversee the entire data lifecycle, from infrastructure setup and data acquisition to detailed analysis and automated reporting, driving business growth through data-driven insights.
Implement robust data quality checks, monitoring mechanisms, and data governance policies to maintain data integrity and security, troubleshooting and resolving any data-related issues efficiently.

We are looking for an Engineering Director to join our engineering leadership team, reporting directly to the VP of Engineering.
In this leadership role, you will own & manage a multi-disciplinary Engineering group spanning AIgo, full-stack, AIOps, QA, and data - accountable for delivery, people, and business outcomes. You will work closely with a Principal Product Manager who sets direction, and directly manage a Product Owner embedded in your team.
Heres what youll be doing:
Own your Engineering group delivery end-to-end - planning, prioritization, dependencies, risks, and outcomes.
Drive accountability: commitments are kept, blockers surfaced early, quality is non-negotiable.
Directly manage all engineers and the Product Owner in your squad, supported by functional guilds.
Run 1:1s, give meaningful feedback, support growth, and build a high-accountability team culture.
Provide technical guidance in close partnership with Principal Architects and senior engineers.
Stay engaged enough to earn trust, spot risk early, and make informed trade-off calls.
Connect your squads work to business outcomes. Always ask why it matters before deciding what to build.
Participate actively in leadership discussions on roadmap, resourcing, and strategy.

Were looking for a Director of Data to lead our evolving Data organization. This is a unique opportunity for an experienced technical leader who thrives at the intersection of leadership and execution. In this role, youll shape the future of our data platform and infrastructure while remaining closely connected to the technology, architecture, and innovation that drive our business forward.
Why Join Us:
Lead a strategically important Data organization during a transformative phase of growth and evolution.
Shape the technical vision, operating model, and future direction of Data Engineering and Data Infrastructure.
Work hands-on with modern data technologies, AI-driven workflows, and emerging platforms while operating at a senior leadership level.
Influence critical company-wide initiatives and partner closely with leaders across R&D, Product, Finance, Support, and GTM.
Join a culture that values ownership, technical excellence, continuous learning, and meaningful impact.
Key Responsibilities
Lead our Data organization in its next phase, driving a lean, high-performing, and highly technical operating model.
Own the technical vision, architecture, and execution across Data Engineering and Data Infrastructure.
Directly manage and mentor a multidisciplinary team, fostering growth, accountability, and engineering excellence.
Provide strong hands-on technical leadership, guiding architectural decisions, reviewing designs, and driving execution on critical initiatives.
Partner with stakeholders across the organization to deliver scalable data products and platforms that support business and product needs.
Drive modernization of our data ecosystem, balancing proven data technologies with emerging approaches in AI, automation, and modern data platforms.
Lead strategic initiatives involving critical infrastructure, platforms, and investments, ensuring scalability, reliability, and operational efficiency.
Champion best practices in data engineering, platform reliability, observability, and operational excellence.

We are looking for a Senior Data & AI Engineer to join a new and growing Data & AI function. You'll work hands-on with models and data architecture, with direct impact on both product-facing AI capabilities and internal data infrastructure. This is a deeply technical role: you'll take ML models from research through production, design scalable pipelines, and collaborate closely with R&D and Product to solve real security problems with AI.
Responsibilities:
Design and implement data architecture, pipelines, and governance foundations
Develop and deploy ML models into production (not just POCs), focusing on areas like vulnerability detection, attack emulation, and security insights
Own model lifecycle end to end: research and experimentation, production deployment, monitoring, and iteration
Partner with Product and R&D to identify and execute high-impact AI use cases within our platform
Evaluate build vs. buy vs. fine-tune decisions for AI capabilities
Define and maintain data quality standards and access policies.

This is a unique opportunity to build and lead a strategic Data & AI capability within a leading consulting firm, shaping its vision, offerings, team, and market presence. The role combines business leadership, solution architecture, and client engagement, helping organizations leverage modern Data & AI platforms to drive transformation and innovation.
Job description
Lead and expand Databricks practice, including strategy, capability development, team growth, and go-to-market initiatives.
Design and oversee enterprise-scale Data & AI solutions, including Lakehouse architectures, data modernization programs, and AI-driven platforms.
Build trusted relationships with senior stakeholders, lead business development efforts, and drive complex technology engagements.
Lead the successful delivery of large-scale Data & AI projects while mentoring and developing high-performing teams.

Required Staff Data Scientist
Job Description
As a Staff Data Scientist, youll play a highly embedded and influential role within our Data Science organisation, partnering closely with Development and Product teams across multiple products within ITOM. Rather than simply responding to predefined requirements, youll bring your own creativity, domain expertise, and ideas to identify opportunities, challenge assumptions, and solve complex problems using real customer data.
What you get to do in this role:
Lead the development and evolution of advanced data science and machine learning capabilities, including noise reduction, anomaly detection, root cause analysis, and new AI-powered product features.
Own complex data science problems end-to-end, from problem definition and ideation through experimentation, model development, evaluation, productionization, and deployment.
Develop advanced algorithms and models using techniques such as machine learning, deep learning, NLP, anomaly detection, and statistical modeling.
Partner closely with Product, Engineering, Quality, and Architects to translate product requirements into scalable, reliable ML solutions.
Drive technical direction and mentor other data scientists, contributing to best practices in modeling, experimentation, evaluation, and ML engineering.
Stay current with advances in AI/ML and identify opportunities to apply emerging technologies to our products.

Alice is a leading platform for Trust & Safety teams worldwide, combining cutting-edge AI with world-class expertise to protect users from the widest spectrum of online harms and keep customers two steps ahead of bad actors.
We are looking for a Senior GenAI Data Scientist with strong hands-on experience in GenAI red teaming, adversarial testing, machine learning, and large-scale data analysis.
You will develop the data science and ML capabilities behind an automated GenAI red-teaming platform. You will analyze and cluster adversarial prompts, identify emerging attack patterns, build models for automated prompt generation and mutation, and develop data-driven methods for prioritizing and evaluating security risks across different AI models.
We are looking for a hands-on technologist with deep expertise in data science: clustering, scaling, machine learning, and statistical analysis.
Key Responsibilities
Build agents that act as data scientists at scale, reasoning, planning, and executing multi-step workflows to generate and analyze adversarial attacks.
Manage and analyze prompt and response data from multiple sources (red-team campaigns, model evaluations, synthetic attacks); clean, curate, normalize, and label it for analysis.
Analyze large volumes of structured and unstructured data to uncover trends, clusters, and anomalies, such as attack families, jailbreak techniques, and previously unseen patterns.
Develop ML models and predictive algorithms to automate red-teaming.
Build evaluation and monitoring pipelines to measure attack success and track model behavior across models and providers.
Use statistical techniques and experiments to validate findings and ensure accuracy and reproducibility.
Take research to production: build reliable, scalable systems optimized for cost and latency, with solid engineering practices (testing, CI/CD, telemetry).

we are looking for a AI Data Lead.
As Data Lead, you will own how data gets turned into decisions across the company - and lead the shift from traditional BI into AI-driven BI, powered by agents that surface insight in real time. You'll work closely with one data engineer today, with room to grow the team as scope expands.
You'll define what the data function looks like when AI is embedded in it, not bolted on - from the underlying infrastructure to the dashboards and agents people actually use. The playbook for AI-native BI is still being written, and you'll write a lot of it.
Key Responsibilities
Data Strategy & Ownership:
Own the vision and roadmap for the data function, including the shift from classic BI to agent-based, AI-driven BI
Set priorities in partnership with senior leadership
Work closely with a data engineer today, with the option to grow the team as the function scales
AI-Driven BI & Agents:
Drive adoption of AI across data workflows - from automating analyses to agents answering business questions in real time
Own the semantic and metrics layer so every dashboard and every agent reads the same definitions
Build in a git-based workflow: dashboards and queries live in git, edited through PRs, built with agents
Expose our data to agents over MCP so business questions get answered without waiting for a dashboard
Define where AI speeds things up - and where human judgment still has to hold the line
Infrastructure & Analytics:
Own the data infrastructure: BigQuery, dbt, pipelines, and data reliability
Lead complex analytics work, A/B testing, and impact measurement, hands-on
Define evals and quality metrics for AI features and agents - not just A/B tests on dashboards
Cross-functional Collaboration
Partner with product, marketing, finance, operations, and engineering to define analytical needs and turn them into solutions
Represent the data function to the organization - senior-level storytelling with data

We are seeking an experienced Data Science Team Lead to join us and play a key role in shaping the future of data security. As a Data Science Lead, you will be part of our Classification team, which lies at the core of our mission - identifying sensitive data and helping customers detect the most critical risks in their cloud environments. Our multidisciplinary team of data scientists.

Responsibilities
Lead the end-to-end lifecycle (design, development, and deployment) of ML models (e.g., NER, LLMs) to advance our data classification and entity recognition capabilities.
Partner with Product to align cutting-edge AI technologies with real-world customer needs and our roadmap.
Architect robust experimentation frameworks to accelerate model iteration, validation, and production deployment.
Utilize extensive datasets to define quality benchmarks and drive continuous performance improvements.
Champion innovation by identifying opportunities for automation and AI-driven features that maximize customer value.

Are you a talented Data Scientist with expertise in image analysis and text reading? Are you passionate about leveraging cutting-edge technologies to drive innovation in the field of electronic component inspection? Look no further!
an industry-leading technology company based in Tel Aviv, we are seeking a skilled Data Scientist to join our dynamic team. As a Data Scientist specializing in image analysis and text reading, you will play a pivotal role in developing and enhancing our AI-driven solutions for quick and accurate component inspection in electronic manufacturing.
Responsibilities
Develop and implement advanced algorithms for image analysis and text reading in the context of component inspection.
Collaborate closely with cross-functional teams to enhance existing models and drive continuous improvement.
Work with large-scale datasets, applying statistical and machine learning techniques to extract meaningful insights.
Stay updated with the latest advancements in the field of image analysis and text reading and apply them to enhance our solutions.