Nuvei

Data Scientist

Nuvei

full-time

Posted on:

Location Type: Hybrid

Location: Tel Aviv-Yafo • 🇮🇱 Israel

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Job Level

Mid-LevelSenior

Tech Stack

AWSAzureCloudKafkaMicroservicesPythonPyTorchScikit-LearnSparkSQLTensorflow

About the role

  • Develop and implement advanced machine learning and generative AI models to solve complex business problems, enhance product offerings, and improve customer experiences.
  • Conduct data exploration and feature engineering to uncover hidden insights and identify opportunities for leveraging data across the business.
  • Collaborate with cross-functional teams to understand business needs and provide data-driven solutions and recommendations.
  • Stay abreast of the latest developments in machine learning and Gen-AI technologies, applying cutting-edge techniques and tools to drive innovation within Nuvei.
  • Evaluate model performance and continuously iterate on and refine models to maintain their accuracy and relevance.
  • Communicate complex data concepts and the results of analyses clearly and effectively to stakeholders across the company.
  • Utilize big data technologies to process and analyze large datasets efficiently, ensuring scalable solutions for data-driven insights.
  • Design and implement big data machine learning solutions using technologies such as Spark, and Kafka for real-time data processing and analytics.
  • Explore and integrate new big data technologies and tools into the existing data ecosystem to improve data analytics and model development processes.
  • Design, build, and productionize agentic AI solutions (single- and multi-agent) for payment use cases such as risk & fraud detection, dispute/chargeback workflows, merchant support, monitoring, and data quality triage.
  • Implement and maintain MCP servers/clients to safely expose tools, data sources, and actions to models; define resources, prompts, schemas, and tool contracts aligned with Nuvei security, compliance, and observability standards.
  • Establish evaluation and LLM observability for agents (task success, reliability, latency, cost, safety), with structured telemetry, tracing, and automated regressions.
  • Implement guardrails and human-in-the-loop mechanisms (policy checks, approvals, safe tool sandboxes, rate limiting, and Write clear documentation and runbooks for agent behaviors, MCP endpoints, versioning, and incident response.

Requirements

  • A Bachelor's or Master's degree in Computer Science, Statistics, Mathematics, or a related field with a strong focus on machine learning or artificial intelligence.
  • At least 3 years of hands-on experience in developing and implementing machine learning models, with a strong preference for candidates with experience in generative AI.
  • Proficiency in programming languages used in data science, such as Python and familiarity with machine learning libraries (e.g., scikit-learn, TensorFlow, PyTorch).
  • Experience with data manipulation and analysis tools, including SQL, and experience working with large data sets.
  • Strong understanding of machine learning principles and algorithms, including supervised and unsupervised learning. Demonstrated ability to apply machine learning techniques to real-world problems, from initial concept through data preparation, model development, and deployment.
  • Excellent analytical and problem-solving abilities, with a keen attention to detail and a data-driven approach to decision-making.
  • Exceptional communication skills, with the ability to convey complex data insights to both technical and non-technical stakeholders.
  • Familiarity with cloud computing services (AWS, Azure, or Google Cloud) and experience deploying models in a cloud environment is a plus.
  • A track record of continuous learning and adapting to new technologies and techniques in data science and AI.
  • Demonstrated experience designing and operating agentic AI systems in production, including planning, tool calling, memory management, and failure recovery.
  • Hands-on experience with MCP concepts (servers, tools/resources, prompts, sessions) or similar tool-exposure protocols; ability to define JSON-schema contracts and enforce authorization, auditing, and quota controls.
  • Practical knowledge of orchestration frameworks (e.g., graph-based or multi-agent frameworks) and integrating agents with microservices, webhooks, queues, and event streams.
  • Experience with RAG, vector stores, and retrieval strategies optimized for tool-using agents; familiarity with evaluation frameworks and LLM telemetry/tracing.
  • Understanding of security and governance for AI systems (PII handling, secrets management, RBAC/ABAC, row-level security, data residency).
Benefits
  • Private Medical Insurance
  • Office and home hybrid working
  • Global bonus plan
  • Volunteering programs
  • Prime location office close to Tel Aviv train station

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard skills
machine learninggenerative AIdata explorationfeature engineeringbig data technologiesSparkKafkaPythonSQLMCP concepts
Soft skills
analytical abilitiesproblem-solvingattention to detaildata-driven decision-makingcommunication skillscollaborationcontinuous learningadaptability