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We are looking for a Senior Data Scientist to lead strategic research initiatives . This individual will be at the forefront of our research, working hands-on to advance our models while also mentoring and collaborating with data scientists across the department.
Responsibilities:
Spearhead strategic research of new cutting edge Machine Learning models
Mentor and advise data scientists.
Design solutions for the companys core mission using Data Science methodologies from various domains
Work in a short life-cycle research and development environment
Generate and test working hypotheses in unexplored territory.

We are looking for a Lead Data Scientist to lead strategic research initiatives. This individual will be at the forefront of our research, working hands-on to advance our models while also mentoring and collaborating with data scientists across the department.
Responsibilities:
Spearhead strategic research of new cutting edge Machine Learning models
Mentor and advise data scientists in the Auto loans research team as well as across the research department
Design solutions for the companys core mission using Data Science methodologies from various domains
Work in a short life-cycle research and development environment
Generate and test working hypotheses in unexplored territory.

Required BI Team Lead
Tel Aviv, Israel
About us:
A global technology company making life-changing financial products and services available to more people nationwide, as it reshapes the financial services ecosystem. By using machine learning, a vast data network and a sophisticated AI-driven approach, we provide comprehensive consumer credit and residential real estate solutions for its partners, their customers, and investors. Its proprietary API and capital solutions integrate into its network of partners to deliver seamless user experiences and greater access to the mainstream economy.
About the Role:
The successful BI Team lead, will play a key role in managing and growing a team responsible for delivering impactful data products and solutions.
As a BI Team Lead, you will oversee the personal and professional development of your team, while also being the main point of contact for client-facing data initiatives. Youll drive data strategy and contribute to new initiatives that support cross-company objectives. This role involves collaborating with product managers, business stakeholders, and leadership to design, develop, and maintain scalable analytics solutions. You will also enhance the companys understanding of key business metrics by building automated tools and insightful visualizations in a rich data environment.
You will also be responsible for integrating AI and machine-learning capabilities into BI solutions, including developing automation processes and AI agents to support decision-making.

a central part of the R&D department is seeking a versatile Senior Data Engineer to take part in leading data vision using a lake-house architecture, and building high-scale solutions for handling and consuming the different data assets of the company.
In this role youll go beyond traditional boundaries, taking on full product responsibilities - from conceptualization and architecture to design, maintenance, and continuous development. You will collaborate closely with stakeholders across the company to ensure our solutions effectively meet their needs.
The ideal candidate will have strong data engineering capabilities, along with software development skills including understanding of designing and managing AWS cloud infrastructure and strong knowledge of different data architectures, methods and tools.
Responsibilities:
Design and development of scalable, reliable, and secure data infrastructure and build ETL pipelines that handle diverse clinical data for research. Write production SQL, Spark jobs and craft schemas that evolve gracefully as research and production questions change.
Automate releases with CI/CD and Infrastructure as Code.
Optimise throughput, latency and cloud cost to meet research timelines at large scale.
Develop and maintain high-quality, scalable, and efficient code while fostering a culture of continuous improvement through regular retrospectives and knowledge sharing.
Take ownership of the full development lifecycle, including requirement gathering, design, implementation, testing, deployment, and ongoing maintenance.
Collaborate with cross-functional teams, including data scientists, data analysts, product managers, regulatory teams, and other developers, to drive the development of new tools and features that support mission.
Explore and adopt new technologies and frameworks that can enhance the capabilities of the Data-Nexus team and the overall data projects .

We are seeking an experienced Solutions Data Engineer who possess both technical depth and strong interpersonal skills to partner with internal and external teams to develop scalable, flexible, and cutting-edge solutions. Solutions Engineers collaborate with operations and business development to help craft solutions to meet customer business problems.
A Solutions Engineer works to balance various aspects of the project, from safety to design. Additionally, a Solutions Engineer researches advanced technology regarding best practices in the field and seek to find cost-effective solutions.
Were looking for a Solutions Engineer with deep experience in Big Data technologies, real-time data pipelines, and scalable infrastructure-someone whos been delivering critical systems under pressure, and knows what it takes to bring complex data architectures to life. This isnt just about checking boxes on tech stacks-its about solving real-world data problems, collaborating with smart people, and building robust, future-proof solutions.
In this role, youll partner closely with engineering, product, and customers to design and deliver high-impact systems that move, transform, and serve data at scale. Youll help customers architect pipelines that are not only performant and cost-efficient but also easy to operate and evolve.
We want someone whos comfortable switching hats between low-level debugging, high-level architecture, and communicating clearly with stakeholders of all technical levels.
Key Responsibilities:
Build distributed data pipelines using technologies like Kafka, Spark (batch & streaming), Python, Trino, Airflow, and S3-compatible data lakes-designed for scale, modularity, and seamless integration across real-time and batch workloads.
Design, deploy, and troubleshoot hybrid cloud/on-prem environments using Terraform, Docker, Kubernetes, and CI/CD automation tools.
Implement event-driven and serverless workflows with precise control over latency, throughput, and fault tolerance trade-offs.
Create technical guides, architecture docs, and demo pipelines to support onboarding, evangelize best practices, and accelerate adoption across engineering, product, and customer-facing teams.
Integrate data validation, observability tools, and governance directly into the pipeline lifecycle.
Own end-to-end platform lifecycle: ingestion → transformation → storage (Parquet/ORC on S3) → compute layer (Trino/Spark).
Benchmark and tune storage backends (S3/NFS/SMB) and compute layers for throughput, latency, and scalability using production datasets.
Work cross-functionally with R&D to push performance limits across interactive, streaming, and ML-ready analytics workloads.
Operate and debug object store-backed data lake infrastructure, enabling schema-on-read access, high-throughput ingestion, advanced searching strategies, and performance tuning for large-scale workloads.

We are looking for a Senior Data Engineer responsible for designing, building, and maintaining the infrastructure necessary for analyzing large data sets. This individual should be an expert in data management, ETL (extract, transform, load) processes, and data warehousing and should have experience working with various big data technologies, such as Hadoop, Spark, and NoSQL databases. In addition to technical skills, a Senior Data Engineer should have strong communication and collaboration abilities, as they will be working closely with other members of the data and analytics team, as well as other stakeholders, to identify and prioritize data engineering projects and to ensure that the data infrastructure is aligned with the overall business goals and objectives.

What You'll Do:
Work closely with data scientists/analytics and other stakeholders to identify and prioritize data engineering projects and to ensure that the data infrastructure is aligned with business goals and objectives.
Design, build and maintain optimal data pipeline architecture for extraction, transformation, and loading of data from a wide variety of data sources, including external APIs, data streams, and data stores.
Continuously monitor and optimize the performance and reliability of the data infrastructure, and identify and implement solutions to improve scalability, efficiency, and security.
Stay up-to-date with the latest trends and developments in the field of data engineering, and leverage this knowledge to identify opportunities for improvement and innovation within the organization.
Solve challenging problems in a fast-paced and evolving environment while maintaining uncompromising quality.
Implement data privacy and security requirements to ensure solutions comply with security standards and frameworks.
Enhance the team's dev-ops capabilities.

As a Senior Data Engineer in our R&D team, you aren't just moving bytes; you are the architect of the world's most comprehensive food-intelligence engine. You will take full ownership of our ingestion pipelines, transforming massive volumes of unstructured web data into the actionable insights our customers rely on. This role requires a builder who can navigate complex anti-bot measures, design resilient distributed systems, and ensure our data remains flawless as we scale.

Key responsibilities:

Own end-to-end architecture and delivery of our web-scale data ingestion pipelines, from resilient scraping through transformation and storage.
Design and maintain scrapers that reliably bypass anti-bot measures and handle dynamic content at scale, adapting quickly as sources change.
Leverage AI coding assistants (Claude Code, Codex) to accelerate development, optimize pipeline logic, and ship faster within titling R&D cycles.
Build and manage distributed, cloud-based data pipelines that support real-time analytics and AI model deployment.
Proactively identify and resolve data quality issues before they reach production, ensuring accuracy and consistency across all sources.
Architect scalable API and system designs that connect pipeline decisions directly to business value and consumer-trend accuracy.
Monitor, troubleshoot, and continuously improve data workflows to keep the engine reliable as we scale.

We are looking for a motivated and business-oriented Data Engineer to join our global Data & BI team.
In this role, you will design, develop, and maintain modern data pipelines and data solutions that support critical business processes across the organization.
You will work closely with global stakeholders, integrate data from multiple sources, ensure data quality and reliability, and contribute to modern data and AI initiatives.
(*Please note, the internal title for this role is Senior Data & BI Specialist, Business Technology.)
Responsibilities:
Design, build, and maintain scalable ETL/ELT pipelines
Develop and optimize complex SQL queries and data transformation processes
Integrate data from internal and external systems, including APIs, databases, and third-party platforms
Own data quality, monitoring, reliability, and governance processes
Investigate and resolve data-related issues while supporting business users
Take ownership of data workflows from design and development through production support
Collaborate with global stakeholders to understand business requirements, analyze data discrepancies, and deliver reliable data solutions
Design, develop, and maintain AI-powered data solutions that support business decision-making and operational excellence
Build and implement monitoring capabilities (e.g. anomaly detection, forecasting, etc.) using modern AI capabilities
Partner with business teams to identify opportunities for applying AI and LLM-based solutions to real-world business challenges
Develop and operationalize AI workflows and data products from proof-of-concept through production deployment

We are hiring a senior individual contributor to join our Data Science team. This is a hands-on role for someone who can take ownership of the full solution, from understanding the problem and building the required data pipelines to developing the model, deploying it, and keeping it reliable in production. You should be comfortable working across data, code, infrastructure, and monitoring independently.
The domain is genuinely hard: noisy sensor and telemetry data, weak and delayed labels, enormous scale, and physical systems that fail in complicated ways. We use whatever technique the problem calls for, from classical machine learning and survival analysis to our own patent-pending deep learning architectures and agentic flows already running in production.
The team moves quickly and operates with a startup mentality: high ownership, short decision paths, and a strong bias toward action. When we encounter a difficult problem, we do not stop at we cant. We ask, How can we?
Moving fast does not mean cutting corners. It means combining resourcefulness and practical judgment with scientific rigor, engineering quality, and production reliability.
We also have proprietary methods for validating results against ground truth, so the feedback loop is real: when a solution works, it ships. You will see your work in production and understand its impact on real fleets.

We are looking for a brilliant Data Engineer- an independent, logical thinker who enjoys solving complex problems and building scalable data solutions. You will own and evolve the data foundations that power Product, Finance, Operations, and Business teams. Working closely with diverse stakeholders, Analysts, and R&D teams, you will serve as a technical partner, translating complex business challenges into robust data models, pipelines, and infrastructure. You should be able to translate business and data requirements into scalable data pipelines and data models, integrating multiple internal and external data sources using the most appropriate technologies. Beyond building pipelines, you will improve data quality, modernize existing data assets, automate manual workflows, and help create a clean, reliable, and scalable data ecosystem that supports the company's growth.
Roles and Responsibilities:
Design and build end-to-end data pipelines - From defining source structures and integrating APIs to delivering clean, trusted datasets that enable analytics, reporting, and operational workflows.
Translate business needs into scalable data solutions based on business priorities and the product roadmap, understand technical requirements, and deliver purpose-built pipelines and tools.
Act as the technical partner for Product, Finance, Operations, and R&D teams, translating business needs into scalable data models, pipelines, and internal tools while ensuring reliable, trusted data across the organization.
Write high-quality, maintainable code, while following best practices and leveraging modern data tooling and CI/CD principles.
Drive data quality and reliability - Monitor, validate, troubleshoot, and continuously improve data quality and pipeline reliability across the data platform.

Were looking for a Data & Analytics Team Lead to manage and grow our data team and own the data layer behind our AI. Youll lead a team of data analysts responsible for neural-network model analysis, model performance tracking, customer-facing and internal BI. Youll act as both the people manager and the technical lead for the team, setting technical direction while staying hands-on.
Youll thrive in this role if youre passionate about turning data into better AI products, enjoy solving complex analytical problems, and like working at the intersection of Data, Analytics, and Artificial Intelligence.
Responsibilities:
Lead the data strategy supporting AI model development, evaluation, and continuous improvement
Define KPIs and monitoring frameworks for AI model performance.
Analyze NN model outputs, build and maintain model-tracking and performance-evaluation workflows
Drive close calibration with the Algo, Product, and Data Engineering teams to align data definitions, pipelines, and metrics
Stay hands-on with SQL, Python, BI tooling, and the modern data stack
Build and own agentic data workflows - designing the context, tooling, and data access that let AI agents reliably query, analyze, and act on company data

Direct employment by the client — you'll be a company employee from day one. What if your next analysis could shape the way a B2C company grows? If you're passionate about turning complex data into meaningful business impact, this opportunity might be exactly what you're looking for. Central Israel, Hybrid: 3 days in the office | 2 days from home We're hiring a Senior Data Analyst In this role, you'll take the analytical lead on a fast-growing B2C product, partnering closely with Product, Marketing, Data Science, and Business teams to drive customer acquisition, optimize performance, and support strategic growth. What you'll be doing: • Analyze customer behavior, acquisition funnels, and marketing performance. • Lead deep-dive analyses and A/B testing initiatives. • Build dashboards and visualizations that drive business decisions. • Work with large-scale datasets and modern data platforms. • Collaborate closely with cross-functional teams to transform data into measurable business impact.

We are looking for a Senior Data Scientist to join AI team, the team behind underwriting decisions, quote-time risk scoring, and portfolio analytics.
In this role, you will own entire research directions: framing the problem, deciding what's worth measuring, designing the approach from first principles, and turning
the result into production signal. The work is production-oriented applied research on hard, real-world datasets where standard recipes don't apply and the right method
often has to be invented for the problem.
What You'll Do:
- Own open-ended research directions end-to-end - from a vague business question to a deployed, validated signal.
- Work across the team's core research areas - risk modeling, environmental and catastrophe modeling, and behavioral modeling - translating complex real-world processes
into reliable predictive signal.
- Deeply investigate existing production models - understand what they actually learn, where they break, and where the headroom is; identify and ship optimizations
grounded in that understanding.
- Design approaches from first principles when off-the-shelf methods don't fit the data.
- Build rigorous evaluations and own the result in production, not just the notebook.
- Document research clearly so findings are reproducible, auditable, and compound over time.