לוח משרות דרושים Senior Data Analyst עבודה היברידית, לחיפוש זה נמצאו 7 משרות

Requirements:
Interested? Here's what we're looking for:

5+ years of experience in fintech or payments fraud analytics. You are a seasoned IC who has scaled fraud programs in complex, high-volume environments.

AI/ML Expertise: Proven experience leveraging Generative AI, LLMs (e.g., RAG, agentic workflows), and Machine Learning to solve real-world risk problems. You don't just use these tools; you know how to build with them.

Technical Powerhouse: Mastery of Python (for data science and automation) and SQL (performance tuning, CTEs, window functions). You are comfortable working alongside engineers and data scientists.

Network Analysis: Deep experience with graph databases (Neo4j, TigerGraph) and link-analysis techniques to identify organized criminal networks.

Demonstrated ability to translate complex quantitative findings into executive‑level insights and influence roadmaps across product, engineering, finance, and support.

Strategic Influence: While this is not a management role, you have a track record of influencing technical roadmaps and advising senior leadership on risk-reward trade-offs.

Advanced data‑visualization skills (Looker, Tableau, Omni, Superset, or equivalent) with a portfolio of self‑service dashboards adopted by the company‑wide.

Domain Depth: Expert knowledge of the payments lifecycle, including CNP, ACH, and RTP risk, as well as the specific fraud challenges of the SaaS and marketplace sectors.

Regulatory Fluency: A solid understanding of PCI DSS, Nacha rules, and the emerging regulatory landscape surrounding AI in financial services.

Prior experience scaling fraud programs in a marketplace, SaaS, or creator‑economy context - Advantage.

Education: Bachelors or Masters degree in a quantitative field (e.g., CS, Statistics, Mathematics, Economics) or equivalent technical experience- Advantage.

Requirements:
3+ years of hands-on experience working with AI - building AI-powered solutions, agents, automations, or AI-driven workflows in a professional setting.
3+ years in roles requiring both technical depth and business acumen - such as solution architecture, systems design, technical consulting, product, operations, CS Ops, customer operations, or technology-driven business transformation.
Strong understanding of Customer Success, support operations, customer operations, or post-sale customer journeys.
Ability to translate business problems into practical AI solutions that are adopted by real users.
Strong technical and architectural thinking, including workflow design, integrations, prompt logic, agent behavior, automation, and scalable systems.
Understanding of AI solution design, including prompt engineering, context engineering, agent design, orchestration, workflow automation, integrations, and runtime behavior.
Experience working with operational systems such as Zendesk, Slack, Notion, CRM, knowledge bases, data tools, workflow automation platforms, or similar tools.
Strong execution mindset, with the ability to move from problem definition to prototype, rollout, measurement, and continuous improvement.
Excellent communication and stakeholder management skills, including the ability to present to leaders, facilitate workshops, coach teams, and translate technical concepts into business language.
Strong analytical skills, with the ability to define KPIs, identify patterns, measure impact, and improve performance over time.
High adaptability, curiosity, and comfort working in ambiguity as AI tools and business needs evolve.
Technical education or equivalent practical experience in Computer Science, Information Systems, Industrial Engineering, Data, Operations, or a related field.