At NiCE, we don’t limit our challenges. We challenge our limits. Always. We’re ambitious. We’re game changers. And we play to win. We set the highest standards and execute beyond them. And if you’re like us, we can offer you the ultimate career opportunity that will light a fire within you.
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?
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: 11941
Reporting into: Manger, Data Science
Role Type: Individual Contributor
About NiCE
NICE Ltd. (NASDAQ: NICE) software products are used by 25,000+ global businesses, including 85 of the Fortune 100 corporations, to deliver extraordinary customer experiences, fight financial crime and ensure public safety. Every day, NiCE software manages more than 120 million customer interactions and monitors 3+ billion financial transactions.
Known as an innovation powerhouse that excels in AI, cloud and digital, NiCE is consistently recognized as the market leader in its domains, with over 8,500 employees across 30+ countries.
NiCE is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, age, sex, marital status, ancestry, neurotype, physical or mental disability, veteran status, gender identity, sexual orientation or any other category protected by law.
Skills Required
- At least 6 years of hands-on experience in data science and machine learning
- Hands-on experience developing solutions using Generative AI, LLMs, or Agentic AI
- Proficiency in Python
- Experience with pandas, NumPy, scikit-learn, Hugging Face Transformers, and LangChain or similar tools
- Strong understanding of supervised and unsupervised learning, regression, classification, clustering, deep learning, feature engineering, model evaluation, overfitting, validation, and model interpretability
- Hands-on experience with LLMs and prompt engineering
- Experience with Hugging Face, LangChain, LangGraph, or similar frameworks
- Experience evaluating generative models
- Strong problem-solving and independent investigation skills
- Strong communication and interpersonal skills
- Experience in financial services, banking, payments, fraud detection, or financial crime
- Experience with cloud computing platforms such as AWS, Azure, or Google Cloud
- Publications or contributions to the data science community
- Experience implementing RAG pipelines with external knowledge bases or vector databases
- Experience building agent-based systems involving planning, tool use, memory, or reflection loops
NICE Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about NICE and has not been reviewed or approved by NICE.
-
Healthcare Strength — Benefits are described as broad and comprehensive, spanning medical, dental, vision, life, disability, and mental-health support. Added programs like FSA options and fitness stipends contribute to a well-rounded health and wellness offering.
-
Retirement Support — A 401(k) is part of the package, sometimes paired with match details that are described as typical to stronger depending on role and time period. Employee stock participation is also positioned as an additional long-term wealth-building component for eligible roles.
-
Flexible Benefits — Flexible work arrangements are emphasized, including hybrid setups and remote options for some roles. Flex scheduling, paid holidays, and paid sick time add to the perceived flexibility of the overall rewards package.
NICE Insights
Similar Jobs
What We Do
NICE (Nasdaq: NICE) is the worldwide leading provider of both cloud and on-premises enterprise software solutions that empower organizations to make smarter decisions based on advanced analytics of structured and unstructured data. NICE helps organizations of all sizes deliver better customer service, ensure compliance, combat fraud and safeguard citizens. Over 25,000 organizations in more than 150 countries, including over 85 of the Fortune 100 companies, are using NICE solutions. www.nice.com.







