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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.

As a Data Engineer, you will:
Infrastructure & Pipelines
Own and maintain our data architecture end-to-end: S3, Databricks compute and administration, pipelines, logging, and our internal tooling
Keep the platform healthy and reliable - the data we serve feeds product decisions and customer-facing AI, so correctness and uptime matter
Integrate new data sources and maintain existing ones, handling the messy realities (format changes, awkward upstream systems like NetSuite, schema drift)
Performance & Cost
Identify bottlenecks and optimize for both compute and cost - parallelize workloads, tune table and cluster settings, and keep our Databricks spend sane as we scale. We use AI coding tools heavily to move fast here, but the engineering judgment is yours
Data Access & Reliability
Build and maintain the semantic layer that exposes our data reliably and consistently to analysts and AI tools, so the same question always returns the same trustworthy answer
Implement PII handling and row- and column-level security so sensitive data stays protected everywhere it's consumed.

We're hiring a Director of Data to lead our company's data function and build our data into a
real competitive moat. You'll report to the CPO, manage and grow our lean data team, and
partner across the leadership table. The role is roughly 70% Build & Operate, 30% Lead &
Influence in year one, shifting toward 50/50 as the team scales.
About us
we are an insurance marketplace and aggregator. We connect thousands of
independent insurance agencies with a wide network of carriers, MGAs, and wholesalers. We
sit at a vantage point neither agents nor carriers have on their own, and turning that asymmetric
view into proprietary intelligence is one of the most important things we'll do over the next
several years.
What you'll do
Lead and grow our data team. Set direction, raise the bar, make their job better.
Make self-service analytics real across our company, so every leader gets to their
answers without queuing behind the data team.
Create a contracts-based partnership with the engineering teams producing source data.
Build a core proprietary data asset that powers our internal and partner-facing
experiences and anchors real conversations with our carriers.
Own the data infrastructure roadmap and the question of how we evolve our data
engineering investment over the next 12-24 months.
Define how AI gets leveraged across our data stack and analytical workflows.
Be the data partner the leadership team actually wants to call.

We are looking for a Backend Engineer with deep data engineering expertise to build and evolve the systems that power product, analytics, experimentation, and AI development.
You will work across production backend services and data infrastructure, taking technical ownership of the full data lifecycle - from event ingestion and real-time processing to orchestration, modeling, quality, and reliable data access. This role combines hands-on backend development with ownership of shared data platform, working closely with backend, frontend, AI, DevOps, analytics, and product teams.
Key Responsibilities:
Build and maintain production-grade Python and Java backend services, APIs, and reactive data-processing pipelines with clear interfaces, resilient failure handling, and comprehensive observability.
Own and evolve batch and streaming data pipelines supporting product analytics, learner insights, experimentation, and AI model training.
Design and maintain trusted data models, shared metrics, and semantic-layer business logic across the analytical data platform.
Define and enforce standards for data contracts, testing, lineage, freshness, and observability.
Develop reliable approaches to schema evolution, backfills, replay, workload distribution, and failure recovery.
Collaborate with DevOps, backend, frontend, AI, analytics, and product teams to deliver reusable data capabilities and maintain clear system boundaries.

At our company, data isn't just for dashboards - it's the nervous system of our future products. As we expand into smart lighting (Oasis) and living tech (Easyplant), we need to process massive streams of IoT signals and power real-time AI. You won't just maintain a warehouse; you will architect the platform that connects our physical products to the digital world.
What youll do
Build the "Brain": Architect the next-gen data platform capable of handling high-volume IoT streams and integrating AI capabilities into our daily operations.
Code the Core: This is a hands-on role. You wont just manage; youll be deep in Python, DBT, and Airflow, building and optimizing the pipelines yourself.
Scale for Complexity: We are growing from one product to a multi-brand ecosystem. You will ensure our data infrastructure evolves to support diverse business lines without becoming a bottleneck.
Democratize Insights: Build a system so robust and intuitive that every engineer, product manager, and marketer can self-serve the data they need to build better products.

Were looking for a Data scientist Expert to join us and spread our power. As a Data Scientist you will be responsible for driving research and development of autonomous AI agents and LLM-powered systems. 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.
Responsibilities:
Lead applied research on AI agents and LLM-driven features in the 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 looking for a Senior Data Scientist to lead the design and implementation of next-generation AI solutions for Lifecycle Marketing.
As a senior member of our team, you will shape methodology, guide product direction under uncertainty, and represent in high-stakes conversations with customers. Youll combine deep expertise in causal inference, reinforcement learning, and experimentation with strong communication skills to drive impact across the company and with our clients.
Responsibilities:
Own the design and methodology of data science solutions for lifecycle marketing, with emphasis on causal inference, uplift modeling, and reinforcement learning.
Lead the development of experimentation frameworks (A/B/n tests, variance reduction, policy evaluation).
Research, prototype, and productionize multi-armed bandits and contextual RL approaches for personalization and timing optimization.
Take a strong, opinionated role in brainstorming sessions, guiding decision-making in areas of high uncertainty.
Represent Voyantis in front of customers, translating complex modeling decisions into clear business value.
Mentor junior and mid-level team members, raising the technical bar across the team.
Collaborate closely with product managers, engineers, and analysts to align data science strategy with business goals.

We are looking for an experienced and visionary Data Engineer to help design, build, and scale our BI platform.
In this role, you will be responsible for developing our data analytics platform - enabling scalable data pipelines and robust data modeling to support real-time and batch analytics to provide insights that serve both business intelligence and product needs.
You will be part of the R&D team, collaborating closely with engineers, analysts, and product managers to deliver a modern data architecture that supports internal dashboards and future-facing operational analytics.
If you enjoy turning raw data into powerful insights and owning the full data lifecycle, this role is for you!
Responsibilities:
Take full ownership of the design and implementation of a scalable and efficient BI data infrastructure, ensuring high performance, reliability, and security.
Design and architect data products, from ingestion to transformation, modeling, storage, and access.
Build and maintain ETL/ELT pipelines, batch and real-time, to support analytics, reporting, and product integrations.
Establish and enforce best practices for data quality, lineage, observability, and governance to ensure accuracy and consistency.
Integrate modern tools and frameworks such as Airflow, Databricks, Power BI, and streaming platforms.
Collaborate cross-functional with product, engineering, and analytics teams to translate business needs into data infrastructure.
Promote a data-driven culture - be an advocate for data-driven decision-making across the company by empowering stakeholders with reliable and self-service data access.

We are looking for a Senior Data Architect to help define and evolve the data architecture of our SaaS platform and core products. You will work closely with product, delivery, and engineering squads to design scalable, reliable data systems, set technical direction for how data is ingested, modeled, stored, and served, and guide teams in making high-quality architectural decisions that balance delivery speed with long-term sustainability.
This is a hands-on, senior technical leadership role: you will spend most of your time shaping data architectures with teams, reviewing data models, pipelines and critical code, and driving shared standards and patterns across the organization, all in an advanced agentic environment.
Responsibilities:
Define and evolve the data architecture for key domains (ingestion, ELT/ETL, data modeling, storage, APIs, integration, observability, governance, and security), including owning the lakehouse/medallion architecture (bronze/silver/gold) and the data flows that move data across layers at scale.
Translate business and product requirements into pragmatic data designs, data contracts, and architecture roadmaps; create and maintain architecture artefacts (data flow/lineage diagrams, ADRs, reference implementations, modeling guidelines).
Evaluate design options and technology choices, articulate trade-offs, and lead decision-making with stakeholders; push forward the agentic mindset and implementation across the data platform.
Partner with squad leads and senior engineers to design data solutions, break down complex problems, and keep implementations aligned with the target architecture; participate in design/tech reviews to ensure NFRs (performance, scalability, data quality, resilience, security, operability) are addressed early.
Provide hands-on support where it matters most: spike and prototype critical data flows, review complex PRs, and help debug tricky production data and pipeline issues.
Collaborate with Product to shape technical feasibility, sequencing, and scope for data-driven roadmap items; communicate complex technical topics in simple language to non-technical stakeholders.
Define and promote data architecture principles, modeling conventions, coding standards, and reusable patterns (shared transformations, libraries, datasets, services) to reduce duplication and technical debt; drive adoption of shared platform capabilities (observability, CI/CD, orchestration, governance, DevOps tooling) across squads.
Ensure data architectures are observable, operable, and resilient by design; partner with DevOps/SRE on deployment, monitoring, data quality, and incident response; identify areas of high technical debt or architectural risk and lead remediation initiatives; define and track technical KPIs tied to architecture decisions.
Act as a technical mentor for senior engineers and tech leads, fostering a culture of thoughtful design, documentation, and constructive technical debate; lead by influence- help teams make better decisions instead of making every decision for them.

we are on a mission to create public transportation systems that provide far greater access to jobs, healthcare, and education. Our platform serves as the technology backbone for modern transit networks, transforming antiquated and siloed public transportation systems into smart, data-driven, and efficient digital networks. With hundreds of agency partners around the world, we are recognized as the leading transportation technology and service provider globally.
As a Software & Data Engineer at our company, you will play a central role in building and evolving the data infrastructure that powers one of the world's leading transportation platforms. You'll work with rich, complex transportation data - from ride bookings and payments to real-time operational signals - designing the pipelines and systems that turn raw data into clean, reliable, and actionable insight across the business. This is a high-ownership role on a talented and deeply motivated engineering team in Tel Aviv, where your work will directly shape how our company understands and improves its service for cities and riders around the world.
About the Role:
Design and build highly scalable, reliable data pipelines that serve clean, structured data across our company's engineering, product, and business teams - ensuring the entire organisation can trust the data it works with
Own the architecture of complex data models that translate messy, real-world transportation data - bookings, payments, driver activity, and more - into systems that are fast, efficient, and built to scale
Lead end-to-end development across the full data lifecycle: from architecture and design through to deployment, monitoring, and continuous improvement
Proactively monitor data quality and reliability, identifying and resolving discrepancies before they reach stakeholders - building the kind of data infrastructure people can depend on
Collaborate with a broad forum of engineers, analysts, and business stakeholders to identify data needs, design POCs, and ship scalable solutions that make a real difference to how our company operates
Contribute to the adoption and evolution of our modern data stack, including DBT, Airflow, Iceberg storage, and AWS big data tooling such as Glue, EMR, and Athena.

We are looking for a highly skilled Senior Data Platform Engineer to join our Data Platform team and play a key role in designing, building, and evolving the companys data infrastructure.

This is a hands-on engineering position focused on developing scalable data platforms, high-volume ingestion pipelines, and the foundational data systems that power analytics, product applications, AI workloads, and large-scale model execution. You will help architect our data lake, build reliable ingestion capabilities at scale, and shape the core infrastructure that supports the companys future growth.

This is an exciting opportunity to work with cutting-edge technologies and have a defining impact on the architecture and evolution of our data platform.

What Youll Do
Build complex, high-volume batch and near-real-time ingestion services while helping evolve the platforms streaming capabilities.
Design and implement data solutions for all application requirements in a distributed microservices environment
Develop and optimize large-scale data pipelines for batch and streaming use cases.
Ensure data quality, compliance, and governance.
Manage and optimize Kubernetes infrastructure, utilizing KEDA to dynamically scale resources for large-scale data processing workloads.
Own the full lifecycle of our data stack using Terraform and Kubernetes, from provisioning to application-level frameworks.
Provide technical guidance for the team, drive best practices around infrastructure, CI/CD, testing, and system design.
Deep-dive into memory management and performance tuning to ensure our large-scale distributed systems are both cost-effective and lightning-fast.

Aura from our company, a large-scale mobile platform, is seeking a highly skilled Senior Data Scientist to join our dynamic AI team. The ideal candidate blends a strong foundation in machine learning, statistics, and software engineering with a passion for modern, AI-accelerated development. You will be responsible for leading the research, design, and end-to-end development of cutting-edge machine learning systems at scale.
What you'll be doing
Innovate at Scale: Design and deploy advanced ML solutions by leveraging our vast, large-scale datasets.
Build & Scale: Develop online, scalable models and tools using machine learning, deep learning, NLP, and modern LLM frameworks.
End-to-End Ownership: Drive projects through their entire lifecycle-from translating complex business questions into technical strategies, all the way to robust production deployment.
Production Excellence: Champion high engineering standards by building, monitoring, and optimizing resilient production workflows.
Cross-Functional Collaboration: Work closely alongside data scientists, ML engineers, product managers, analysts, and developers to solve complex, multi-faceted problems.

We are looking for a Senior Fraud Analyst to serve as the technical cornerstone of our Fraud Prevention team.
In this role, you won't be managing a team; youll be managing the technical evolution of our fraud defenses. Reporting directly to the Fraud Prevention Director, you will act as a high-level individual contributor, bridging the gap between data science, engineering, and risk strategy. You will be responsible for pioneering the use of AI and advanced analytics to protect our community and ensure our platform remains the safest place for independent businesses to grow.
Here are a few of the things you'll do:
Technical Strategy & Architecture: Partner with the Fraud Prevention Director to define the long-term technical roadmap, moving us toward an AI-first, autonomous fraud detection ecosystem.
AI & LLM Integration: Design and implement Generative AI agents and LLM-powered workflows to automate complex forensic investigations, reducing the time-to-detect for emerging fraud vectors.
Advanced Detection Modeling: Develop and prototype sophisticated ML models and graph-based heuristics to identify collusion, synthetic identities, and fraud rings.
Cross-Functional Technical Lead: Serve as the primary technical consultant to Product and Engineering, ensuring that new payment features (like RTP or international expansion) are built with scalable, AI-driven safeguards from day one.
Expert Forensics: Act as an escalation point on high-stakes, large-scale fraud attacks, utilizing advanced Python and network analytics to deconstruct and mitigate threats.
Data Excellence: Set the standard for the fraud teams technical stack. You will optimize our SQL/Python environments and ensure our data infrastructure is capable of supporting real-time AI inference.

We are on the search for a Marketing Analytics Lead who will join our Data team in Tel Aviv. As a Marketing Analytics Lead in a Data-Driven company, you will have a significant opportunity for impact and drive the company to new heights. You will influence decision-making processes throughout marketing budget decisions, new user journeys, be a partner to cross-functional teams within data, marketing & Top of Funnel, and drive strategic business decisions that shape the direction of the company.
Here are a few of the things you will do:
Own end-to-end analytics for marketing and product growth initiatives, directly supporting business strategy and growth, including and not limited to acquisition, lifecycle, and user onboarding.
Act as the primary data owner for the planning, monitoring, and measuring a variety of marketing initiatives, ensuring accuracy, consistency, and trust in decision-making across stakeholders, enabling your stakeholders to learn from data and iterate with confidence.
Translate complex datasets from multiple sources into clear, actionable insights with measurable business impact.
Proactively initiate and perform ad hoc research and deep-dive analyses to surface unknown business opportunities to inform strategic and operational decisions.
Partner with marketing, product, finance and company leadership to drive cross-functional, data-driven outcomes.
Design, improve, and scale analytics infrastructure, data pipelines, and workflows to suit your analytics needs; work hands-on using tools such as SQL, DBT, Looker, and partner closely with Data Engineering and Data Science teams.
Design, execute, and evaluate A/B tests using rigorous statistical methods and well-defined KPIs, including ownership of appropriate KPI selection.
Present insights and recommendations to senior stakeholders with clarity and influence, through written communication, presentations, and via dashboards.
Contribute expertise to shared analytics standards, best practices, and knowledge forums (e.g., Data Guild).

we are looking for a Data Software Engineer.
Full-stack engineer with a soft spot for geometry: build the data and product systems that power automation across frontend and backend.