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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.

Were hiring an AI Backend Engineering Manager to guide and grow a high-impact ML team driving AI-powered innovation across B2B SaaS platform. Youll lead the design and delivery of AI solutions while mentoring engineers and setting the technical direction for AI-first development at scale.
This is a leadership role with a balance of hands-on engineering and team management, perfect for someone who thrives on solving technical challenges, inspiring a team, and shaping the future of AI in fintech automation.
What You Will Do:
Lead & Mentor: Manage, mentor, and grow a team of AI/ML/Backend engineers, fostering technical excellence and career development.
Set Technical Direction: Define the ML strategy, ensuring best practices in architecture, frameworks, and operationalization.
Build and deploy AI-based solutions: Oversee the development and deployment of GenAI/LLM-powered solutions that address real-world challenges across products.
Scale & Operationalize: Establish scalable ML infrastructure, CI/CD, observability, and data pipelines for high-availability production systems.
Collaborate Cross-Functionally: Partner with product managers, engineers, and business stakeholders, clearly communicate progress, challenges, and outcomes.

We are looking for a strategic product leader to head our Data Platform domain - a core area of our offering. This role is critical to the companys growth, driving both short-term impact and long-term vision for managing and leveraging massive amounts of structured and unstructured clinical data. In this role, you will lead the product strategy and execution for the domain, while guiding and mentoring product managers within the team. You will work closely with Engineering, Data Science, Clinical Experts, the rest of the Product group, as well as partners and strategic customers, shaping how our platform operates and scales to meet the needs of our growing business.

Responsibilities
Define and drive the roadmap for our Data Platform, balancing short-term business needs with long-term scalability and platform strategy.
Own the product vision for data ingestion, processing, and access, ensuring the platform supports all product groups and business initiatives.
Lead and mentor a team of product managers, fostering growth, collaboration, and a culture of ownership and impact.
Support your team in translating complex technical and data requirements into clear product specifications, prioritizing initiatives that maximize business impact.
Partner closely with Engineering, Data Science, Clinical Experts, Customer Success, the entire PM group, and external partners and strategic clients, to design and prioritize initiatives, ensuring data quality, performance, and usability.
Drive cross-team technical initiatives end-to-end, coordinating dependencies and aligning stakeholders across the organization.
Establish key metrics to measure platform performance, adoption, and impact on product outcomes.

At our company, business users don't file ticket requests for dashboards. They ask questions in natural language and get answers directly - through Claude, connected to Looker and our other data tools over MCP. Claude is also our primary tool for writing code here.

That only works if what sits underneath is right. This role owns that foundation: the event instrumentation in our products, the pipelines feeding the warehouse, the models that give the data meaning, and the tests that prove it's correct. You're not producing charts - you're making hundreds of self-served answers trustworthy.

It's an engineering role, but not one you can do from behind the data. You'll need to understand the business well enough to know what a metric should mean before you model it.

Responsibilities
Instrumentation - Own product event tracking end-to-end: define the tracking plan with Product, drive implementation with our frontend and backend teams, audit what's actually firing, and build validation that catches regressions at deploy time rather than three months later.
Pipelines and warehouse - Build and operate batch and streaming pipelines into the warehouse; own its transformation layer, performance, data quality monitoring, and alerting.
Semantic layer - Own metric definitions and the modeled layer our AI and BI tooling query against, so core business terms resolve to one thing company-wide. Design models that hold up under open-ended questions, not just the ones you anticipated. Own lineage, documentation, and governance.
Business partnership - Work directly with Product, Sales, Customer Success, and Finance to understand what they're trying to measure, and push back when a proposed metric won't survive contact with reality.
Our stack
Redshift, Looker, Airflow, Kafka, AWS, Kubernetes, Python, SQL, TypeScript - with Claude and MCP as the layer connecting people to all of it.

We are looking for a BI Lead to join our Data team. You will define the metrics the company runs on, make sure they are modeled correctly, and set the technical standards our analysts work with. You'll work directly with Sales, Product, and Marketing leaders to align on what we measure and why. As our technical lead for analytics, you own the definitions and standards that drive business decisions across.
As our BI Lead, you'll own the analytics function end-to-end: defining what we measure and why, setting technical and organizational standards for how we measure it, and empowering teams across the organization to make data-driven decisions. You'll be hands-on technically while also developing processes that scale.
Key Responsibilities:
Define, own, and validate business logic behind core KPIs with executives, align definitions with relevant stakeholders, and once approved, model them in the data warehouse to ensure consistent, trusted metrics across all teams.
Work closely with stakeholders across the company (Sales, Product, Marketing, etc.) to understand what needs to be measured, why and how.
Collaborate with Data Engineers and Business Analytics to design scalable data pipelines, data models, and semantic layers that support analytics, experimentation, and advanced modeling.
Lead the evaluation, selection, and optimization of BI and data infrastructure in collaboration with data engineering.
Build and maintain the cross-company dashboards and reports that business leaders actually rely on to make decisions.