Specialist Data Scientist, Actimize

So, what’s the role all about?

We are seeking a Specialist Data Scientist (8 + yrs experience) with a strong track record of turning state-of-the-art Generative AI and classical ML techniques into production value. The Specialist Data Scientist will be responsible for developing Machine Learning models and agentic AI systems that augment fraud detection capabilities, combining LLMs, traditional ML, and domain expertise into scalable, reliable products.

How will you make an impact?

• Develop and execute advanced analytics projects from end to end, including data collection, preprocessing, model development, evaluation, and deployment.
• Design and develop predictive and generative models to extract actionable insights from large and complex tabular datasets.
• Utilize statistical techniques and quantitative analysis to identify trends, patterns, and correlations within the data.
• Perform feature engineering and explore advanced representations of transactional and behavioural data.
• Evaluate models using appropriate fraud-focused metrics, including detection performance, precision/recall, stability, generalization, and operational impact.
• Design and build agentic AI workflows, including:
• Multi-step reasoning, planning, and orchestration
• Tool/function calling and tool-using agents
• State and memory management
• Autonomous workflows for investigation and decision support
• Human-in-the-loop controls and decision making
• Implement evaluation frameworks for LLMs and agents including quality, safety, and hallucination detection.
• Translate business problems into analytical solutions in partnership with Product, Engineering, and domain SMEs.
• Clearly communicate research findings, model results, trade-offs, and recommendations to both technical and non-technical stakeholders.
• Collaborate closely with Data Scientists, Engineering, Product, and domain experts.
• Stay current with advances in Agentic AI, LLM architectures, reasoning systems, and ML research.

Have you got what it takes?

• Minimum of 6 years of hands-on experience in data science and machine learning, with hands-on experience developing solutions using Generative AI, LLMs, or Agentic AI
• Proficiency in programming languages such as Python , as well as experience with data manipulation and analysis libraries (e.g., pandas, NumPy, scikit-learn, Hugging Face - Transformers, LangChain etc.).
• Strong understanding of machine learning techniques and algorithms, including supervised and unsupervised learning, regression, classification, clustering, and deep learning, feature engineering, model evaluation, overfitting, validation, and model interpretability.
• Hands-on experience with:
• LLMs and prompt engineering
• frameworks like Hugging Face, LangChain, LangGraph / similar
• evaluation techniques for generative models
• Excellent problem-solving skills and ability to work independently as well as collaboratively in a fast-paced environment.
• Ability to independently investigate a problem, formulate hypotheses, design experiments, and derive actionable conclusions.
• Strong communication and interpersonal skills, with the ability to effectively communicate complex technical concepts to diverse audiences.

You will have an advantage if you also have:

• Experience in financial services, banking, payments, fraud detection, or financial crime
• with cloud computing platforms (e.g., AWS, Azure, Google Cloud) and related services for building and deploying machine learning models.
• Publications or contributions to the data science community, such as conference presentations, research papers, or open-source projects.
• Experience in implementing RAG pipelines, combining LLMs with external knowledge bases or vector databases.
• Experience building agent-based systems (planning, tool use, memory, reflection loops)

What’s in it for you?

At NiCE, we work according to the NiCE-FLEX hybrid model, which enables maximum flexibility: 2 days working from the office and 3 days of remote work, each week. Naturally, office days focus on face-to-face meetings, where teamwork and collaborative thinking generate innovation, new ideas, and a vibrant, interactive atmosphere.

Requisition ID: 11941
Reporting into: Manger, Data Science
Role Type: Individual Contributor