Senior Data Scientist, Actimize

So, what’s the role all about?

As a Senior Data Scientist, you will be responsible for designing, developing, and delivering machine learning and Generative AI solutions that enhance fraud detection capabilities. You will work closely with Product, Engineering, and domain experts to translate business challenges into scalable AI-driven products, combining LLMs, classical ML techniques, and domain knowledge into production-grade systems

How will you make an impact?  

• Design and develop end-to-end machine learning solutions – from data collection and preprocessing to model development, evaluation, and deployment.
• Build predictive and generative models to extract actionable insights from large and complex datasets.
• Apply statistical analysis and quantitative techniques to uncover patterns, trends, and correlations in data.
• Utilize statistical techniques and quantitative analysis to identify trends, patterns, and correlations within the data.
• Design and build agentic AI systems, including:
  • multi-step reasoning pipelines
  • tool-using agents
  • autonomous workflows for investigation and decision support
• Develop RAG-based architectures, integrating LLMs with structured and unstructured data sources.
• Translate business problems into analytical solutions in partnership with Product, Engineering, and domain SMEs.
• Stay current with advances in Agentic AI, LLM architectures, reasoning systems, and ML research.

Have you got what it takes? 

• Minimum of 4-8 years of hands-on experience in data science and machine learning, with at least 1 year of experience in Generative AI development.
• 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.
• 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.
• 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 working in industries such as finance, banking.
• Familiarity 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)
• Hands-on experience with vector databases (e.g. Pinecone) and embedding techniques.

What’s in it for you?

Join an ever-growing, market disrupting, global company where the teams – comprised of the best of the best – work in a fast-paced, collaborative, and creative environment! As the market leader, every day at NiCE is a chance to learn and grow, and there are endless internal career opportunities across multiple roles, disciplines, domains, and locations. If you are passionate, innovative, and excited to constantly raise the bar, you may just be our next NiCEr!

 Enjoy NiCE-FLEX!

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: 10972
Reporting into: Manger, Data Science
Role Type: Individual Contributor