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we are looking for a Manager, Data Science & Research.
What will you do:
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

Were looking for a BI & Data Engineering Team Lead to join our BI team and take end-to-end ownership of high-impact analytics foundations while mentoring a team of 4-6 talented BI Data Engineers. This role sits at the core of how measures success, makes decisions, and scales-turning raw data into trusted, business-critical insights used across Product, GTM, and Finance.
In this role, you'll combine people leadership with hands-on technical depth (roughly 30% of your time), owning the roadmap, architecture, and delivery of BI platform. Youll shape how AI and agentic workflows transform the way BI is built and consumed, helping raise the bar for analytics engineering across the company.
Hands-on experience using GenAI to improve analytics engineering workflows, automate development processes, and increase delivery speed is a must for this role.
This role is based in Tel Aviv. We work in a hybrid model, with 3 days a week in the office.

Were looking for a Senior BI Data Engineer to join our BI team and take end-to-end ownership of high-impact analytics foundations. This role sits at the core of how measures success, makes decisions, and scales - turning raw data into trusted, business-critical insights used across Product, GTM, and Finance.
Youll design and evolve data models, pipelines, and the BI layer, work closely with Data Science and business stakeholders, and help raise the bar for analytics engineering across the company.
This role is based in Tel Aviv. We work in a hybrid model, with 3 days a week in the office.

We're looking for a Senior Data Platform Engineer to join the Data Platform team, which owns the infrastructure every data team at Lusha runs on and sits between DevOps and the Data groups. You'll be the Databricks admin (Unity Catalog, compute, governance, cost), the Confluent (Kafka) and CDC admin, and own Airflow, Elasticsearch, the databases, the data S3 estate, and the Kubernetes cluster underneath. Your job is to make the platform fast, cheap, governed, and boring: if it's broken, you fix it, if it's manual, you automate it.
Hands-on experience using AI coding tools daily, and building or integrating LLM and agent tooling into real workflows, is a must for this role.
This role is based in Tel Aviv. We work in a hybrid model, with 3 days a week in the office.

our company seeks an experienced Senior Staff Data Engineer to join our AI and Data Solutions unit and champion an AI-first strategy. You will spearhead the development of Data Lakehouse processes, model core product domains, and define data engineering best practices across the organization. Serving as a technical project lead, you will provide strong direction and collaborate with Data Science, Analytics, R&D, and IT teams to elevate onboarding workflows. This role demands a proactive approach to optimizing system capabilities and driving cross-functional data initiatives.
Key Responsibilities
Own the design, implementation, and optimization of scalable Data Lakehouse and Data Warehouse architectures across diverse cloud ecosystems.
Spearhead the development of robust ETL/ELT pipelines and data ingestion processes utilizing SQL, Python, PySpark, and DBT.
Apply advanced data modelling techniques to structure complex data assets into optimized facts, dimensions, and partitions.
Partner with cross-functional leadership across data science, analytics, R&D, and IT to identify requirements and improve workflows.
Orchestrate complex data workflows combining tools like Airflow and DBT with advanced Gen-AI development workflows using CloudCode.
Define, document, and popularize data engineering best practices, design patterns, and data quality standards across the unit.
Evaluate and implement modern data technologies spanning vendor-specific and open-source landscapes including GCP, AWS, and Apache Iceberg.
Provide technical direction and hands-on guidance to ensure high-performance execution, reliable pipeline delivery, and proactive problem-solving.

Required Principal/ Senior Data Scientist - LLM Agents
Job Summary
As a Data Scientist, you will apply your expertise in software engineering, LLM agents, and cybersecurity to build new defense techniques against cyber-villains. You will be a driving force in designing and developing groundbreaking, Agentic LLM-based security solutions that block attacks before they begin. Join our innovative team to shape the future of cybersecurity and impact millions of customers.
Important: this role requires a unique combination of hands-on software engineering skills as well as previous experience with designing and delivering LLM-driven products.
Key Responsibilities:
Contribute to a diverse and highly skilled research group that pioneers state-of-the-art technologies to protect our customers.
Utilize analytical rigor, statistical methods, programming, and data modeling to analyze vast amounts of data, applying your cybersecurity knowledge to guide our focus and approach.
Design and implement agentic LLM solutions to face modern cybersecurity challenges.
Decompose complex problems scientifically and provide actionable insights and recommendations to both technical and non-technical stakeholders.
Lead and collaborate on end-to-end projects within the team and across engineering and product teams, from initial ideation to final deployment.

Required Principal Data Engineer (Cortex)
Job Summary
As a Principal Data Engineer, you will be integral to the security research group, designing, building, and maintaining the data pipelines and data frameworks that are the backbone of our cyber attack detection capabilities. You will work closely with top security and AI researchers, enabling their work and seeing the direct impact of your contributions on our services and the day-to-day effectiveness of the research team.
Key Responsibilities:
Lead the design and implementation of end-to-end, complex data pipelines and data platforms in cloud environment.
Collect, analyze, and translate complex data requirements from various stakeholders including data analysts, developers, and Cyber security researchers.
Develop robust, scalable Cloud based data solutions using Python and distributed processing frameworks such as Apache Beam (Dataflow) , GKE , Spark , etc.
Utilize AI as part of the development cycle, including generating, reviewing, and testing code via prompts.
Model and manage data within cloud MPP databases and data lakes such as BigQuery, Redshift, or Snowflake.

Required Senior Principal Data Scientist - LLM Agents (Cortex)
Job Summary:
Are you passionate about harnessing cutting-edge data science techniques to protect the world from cyber threats? Do you thrive in the dynamic world of cybersecurity? If so, we invite you to join our innovative and forward-thinking team, where you'll have the opportunity to shape the future of cybersecurity and impact millions of customers.
As a Senior Principal Data Scientist, you will be a technical leader and hands-on architect, bridging the worlds of advanced data science, robust software engineering, and next-generation AI. You will bring a deep, diverse background in classical machine learning algorithms alongside cutting-edge LLM agent architectures to build resilient, production-grade defense techniques against cyber-villains. Operating as a premier technical authority, you will drive the vision, design, and large-scale development of our groundbreaking, Agentix LLM-based security solutions that block attacks even before they begin.
Key Responsibilities:
Serve as a hands-on technical compass for a diverse, elite product-oriented research team, pioneering state-of-the-art technologies and setting the engineering standards for AI/ML excellence across the organization.
Design, implement, and optimize robust Agentic LLM solutions and multi-agent workflows engineered to autonomously counter modern, sophisticated cyber threats.
Oversee and actively contribute to the entire end-to-end lifecycle, moving seamlessly from ambiguous research concepts and POCs to high-throughput, low-latency production deployments.
Build and enforce comprehensive frameworks for continuous real-time monitoring, evaluation, and guardrails to track model drift, latency, and agent behavior in production environments.
Decompose highly complex, multi-layered algorithmic problems into actionable technical roadmaps and strategic insights for both deeply technical engineers and executive business stakeholders

We are looking for a talented and experienced Mid-Level Data Engineer with a passion for data and cloud technologies to join our team. In this role, you will be a key player in designing, developing, and maintaining our AWS and Databricks-based data platform. You will bridge the gap between robust Data Engineering, Database Administration (DBA), and high-performance Analytics Engineering.

The ideal candidate understands the Lakehouse architecture, has experience managing modern cloud data warehouses like Snowflake, and possesses the ability to build scalable ETL pipelines that drive data-driven business decisions.

Key Responsibilities

End-to-End Pipelines: Develop and maintain complex ETL/ELT pipelines using Python/PySpark on the Databricks platform, as well as loading and transforming data within Snowflake.
Data Architecture: Implement and manage data layers following the Medallion architecture (Bronze, Silver, Gold) using Delta Lake.
Optimization & Analytics: Set up and manage Databricks SQL Warehouses, perform query optimization, and utilize internal visualizations for rapid data exploration.
Cloud Infrastructure: Leverage AWS cloud services to manage data storage, compute resources, and secure data movement.
DBA & Performance Tuning: Act as a custodian for our data platform-managing indexing, clustering, vacuuming, and performance tuning across both Delta Lake and relational/warehouse environments to ensure cost-efficiency and high speed.
Data Modeling: Design data models (Star Schema / Snowflake) in the Gold layer to ensure optimal performance for BI tools (e.g., Power BI, Tableau).
Data Governance: Manage metadata, permissions, and lineage using Unity Catalog and platform-specific access controls.
Quality Control: Implement automated Data Quality tests as an integral part of the CI/CD data pipelines.

We are looking for a highly skilled and visionary Senior Machine Learning Engineer to lead the architecture, design, and deployment of enterprise-grade AI/ML projects on AWS. In this role, you will take full technical ownership of advanced AI initiatives, leveraging both native managed services (such as Amazon SageMaker and Bedrock) and custom-built GenAI models to deliver transformative predictive insights and automation to our customers.

As a Senior ML Engineer, you will bridge the gap between complex data engineering and state-of-the-art data science. You will drive the design of scalable MLOps architectures, optimize high-volume data pipelines, and act as a trusted technical advisor to our clients. You will work closely with solutions architects, project managers, and data scientists, while also mentoring junior and mid-level engineers to elevate the team's technical capabilities.

Responsibilities

Architect and Lead ML Solutions: Spearhead the end-to-end architecture, development, and production deployment of robust Machine Learning models, including advanced predictive analytics, NLP, and Generative AI/RAG systems.
Enterprise MLOps & Automation: Define, design, and implement enterprise-grade MLOps strategies. Establish CI/CD pipelines for ML, automated model training, monitoring, versioning, and governance at scale.
AWS AI/ML Mastery: Architect innovative solutions leveraging AWS AI/ML managed services (e.g., SageMaker, Bedrock) to accelerate time-to-market while ensuring high performance and cost-efficiency.
Advanced Data Engineering: Lead the design of highly scalable infrastructure for extracting, transforming, and loading (ETL) data from diverse sources to support complex ML feature stores and model training.
Unstructured Data & Vector Search: Architect systems for the optimal ingestion, processing, and semantic retrieval of unstructured data (text, images, documents) using Vector Databases (e.g., OpenSearch, Pinecone) and graph-based reasoning.
Strategic Advisory & Collaboration: Act as a trusted AI advisor to external enterprise customers and internal C-level executives. Translate complex business constraints into scalable ML architectures and guide clients through their AI adoption journey.
Technical Leadership & Mentorship: Mentor mid-level and junior engineers, establish coding and architectural best practices, and foster a culture of continuous learning and innovation within the team.

Architectural leadership of the enterprise DWH project in an AWS cloud environment. The role focuses on designing robust data infrastructure, establishing the technological roadmap, and enabling seamless large-scale data processing to support BI and AI initiatives.

Key Responsibilities:

Lead the architectural design and implementation of the new enterprise DWH project.
Design, develop, and optimize complex cloud-based data solutions for processing massive datasets.
Select and implement the optimal AWS services (Redshift, Glue, Athena, EMR) and data formats (Parquet, Iceberg) for the core data stack.
Provide technical leadership, mentorship, and professional guidance to the Data Engineering team.
Collaborate closely with development teams, Data Scientists, and end-users to define requirements and deliver innovative Data and AI solutions.

Integration into the development team for a core DWH project and various AI projects. Responsibilities include the ingestion of large volumes of new data, followed by deep understanding and analysis of data in close collaboration with Data Scientists. Design, development, and optimization of critical, diverse, and large-scale data pipelines - in both cloud and on-premise environments.



Key Responsibilities:

Take responsibility for the ingestion of large volumes of new data.
Conduct deep understanding and examination of data in close collaboration with Data Scientists.
Design and develop critical, diverse, and large-scale data pipelines and processes.
Deploy and optimize data solutions across both cloud and on-premise environments.

You and your team will work primarily with dbt, BigQuery, Looker, and GitHub, while using AI-enabled tools such as Cursor, MCP integrations, n8n, and OpenClaw to automate workflows and scale how the team works.

Success in this role requires strong leadership, technical depth, business understanding, and the ability to turn complex data into clear, actionable recommendations.

Key Responsibilities
Lead, manage, and develop a team of Data Analysts, including setting goals, providing feedback, and supporting their professional growth.
Own the teams priorities and analytical roadmap, ensuring the team focuses on the highest-impact business needs.
Define and drive technical and analytical standards across data modeling, SQL, dbt, testing, code reviews, and BI.
Partner with stakeholders and senior leadership to understand business needs, define KPIs, and translate data into actionable recommendations.
Lead high-impact analyses and guide the development of reliable, scalable data models and Looker dashboards.
Ensure data quality and lead investigations into anomalies, tracking issues, and inconsistent metrics.
Drive AI-native ways of working by turning repeatable analyses and processes into reusable, automated workflows.
Stay hands-on with data, code, and analysis when tackling complex or high-impact problems.

In this role, you will define and drive the vision, strategy, and execution of data and analytics products that support our Marketing, Growth, and Acquisition teams. You will operate at the intersection of business, analytics, data science, and AI, translating marketing challenges and business questions into scalable data products, clear KPIs, and measurement frameworks that improve acquisition efficiency, ROI, and long-term revenue growth.
You will lead cross-departmental initiatives, partner closely with Marketing leaders, Data Scientists, Data Engineers, Analytics teams, and Product Managers, and ensure that advanced modeling, analytics, and AI capabilities are deeply embedded into day-to-day marketing decision-making.

Key Responsibilities
Marketing Data Product Ownership
Own the vision, roadmap, and delivery of Marketing Data Science and Analytics products
Align initiatives with business goals such as acquisition efficiency, ROI optimization, revenue growth, and funnel performance.
Act as the single point of ownership for marketing-related data, analytics, and data science products across teams.
Define data requirements, metrics, and success criteria for new initiatives, including identifying gaps in existing data.
Collaborate with Data Engineers and Analytics Engineers to design scalable data pipelines, data models, and semantic layers that support analytics, experimentation, and advanced modeling.
Prioritize initiatives based on business impact, scalability, data maturity, and clarity of success metrics.
Business Analytics, Data Science & AI-Driven Marketing Optimization
Define and own the business logic behind marketing KPIs, ensuring clear, consistent, and trusted metrics across teams.
Work closely with stakeholders to understand what needs to be measured, why and how.
Lead data science, analytics, and AI initiatives that optimize marketing performance
Own and evolve core marketing models including attribution, MMM, LTV prediction.
Define success metrics and measurement frameworks for models, experiments, and AI-driven decisions.
Drive experimentation frameworks (A/B tests, geo-experiments, uplift modeling) to continuously improve performance and decision quality.
Design and deploy AI-powered and agentic solutions to automate and scale marketing workflows such as budget allocation, campaign optimization, and creative testing.
Ensure solutions are production-ready, measurable, explainable, and actionable for business stakeholders.
Translate complex model outputs into clear, trusted insights for business users.

We are looking for a Software Engineer to help design and develop the core services and applications that drive our data capabilities. In this role, you will build high-quality, scalable software; contribute to the architecture of our next-generation data systems; and collaborate with research and product teams to turn cutting-edge ideas into production-ready features.
Responsibilities:
Design, develop, and maintain scalable backend services and components that power our data workflows, analytics, and product features.
Build high-quality internal tools and applications that improve engineering workflows and enable data-driven development across the organization.
Contribute to the architecture and evolution of our new data platform with a strong focus on clean design, testability, maintainability, and performance.
Collaborate closely with security researchers, analysts, and product managers to translate innovative cybersecurity concepts into reliable, production-ready software.
Apply engineering best practices across the stack - including code quality, testing, observability, versioning, and documentation - to ensure system robustness as we scale.