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 looking for talented and motivated Data Scientists who are passionate about solving complex fraud‑related problems using advanced analytics and machine learning. You are someone who thrives on exploring large datasets, uncovering hidden patterns, and building predictive models that make a real business impact. You enjoy collaborating with cross‑functional teams, experimenting with new techniques, and delivering scalable analytical solutions.
If you love transforming raw data into actionable insights and want to be part of a high‑performing analytics team at NICE Actimize, this role is for you.
How will you make an impact?
You will join a dynamic team of highly skilled Data Scientists and Fraud Analytics experts working on cutting‑edge analytical solutions. In this role, you will:
- Work with large, complex datasets to analyze fraud cases and identify inconsistencies.
- Build, validate, and optimize machine learning models for fraud detection and prevention.
- Research data patterns to predict fraudulent transactions and improve model performance.
- Enhance existing models using advanced computational algorithms and techniques.
- Develop compelling visualizations that help stakeholders understand trends and insights.
- Collaborate with business teams, engineers, and stakeholders to deliver scalable analytical solutions.
- Drive continuous improvement by staying updated with the latest advancements in Data Science and ML.
- Communicate analytical findings clearly to both technical and non‑technical audiences.
- Participate in critical discussions, advocate technical solutions, and support model deployment.
- Contribute to innovation forums and knowledge‑sharing initiatives across NICE.
Have you got what it takes?
- 4 to 8 years of relevant Data Science experience.
- Strong analytical, problem‑solving, and communication skills.
- Ability to explain complex analytical concepts to non‑technical stakeholders.
- Experience working in agile, multi‑disciplinary teams.
- Self‑driven, collaborative, and committed to delivering high‑quality outcomes.
Qualifications & Skills
Core Skills
- Advanced degree in Statistics, Mathematics, Computer Science, Engineering, or related fields.
- Strong knowledge of statistical techniques (regression, feature selection, time series, etc.).
- Proficiency in SQL and Excel.
- Strong programming skills in Python (3.7+).
- Hands‑on experience with ML techniques (clustering, decision trees, boosting, etc.).
- Experience developing and deploying classification and regression models at enterprise scale.
- Understanding of logistic regression and regularization techniques.
- Familiarity with ML‑Ops frameworks or containerized environments (Kubernetes is a plus).
- Experience troubleshooting production data and deployed models.
- Exposure to cloud platforms (AWS, Azure preferred).
- Experience with visualization and presenting insights clearly.
Additional Desired Qualifications
- Experience in fraud analytics, financial crime, or risk management models.
- Knowledge of financial systems and data standards.
- Experience with containerized model development using Kubernetes.
- Exposure to banking or financial services domain.
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 Details
- Requisition ID: 11668
- Reporting into: Tech Manager, Actimize
- 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
- 4 to 8 years of relevant Data Science experience
- Advanced degree in Statistics, Mathematics, Computer Science, Engineering, or a related field
- Strong knowledge of statistical techniques, including regression, feature selection, and time series
- Proficiency in SQL and Excel
- Strong programming skills in Python 3.7 or later
- Hands-on experience with machine learning techniques such as clustering, decision trees, and boosting
- Experience developing and deploying classification and regression models at enterprise scale
- Understanding of logistic regression and regularization techniques
- Familiarity with ML-Ops frameworks or containerized environments
- Experience troubleshooting production data and deployed models
- Exposure to cloud platforms, preferably AWS or Azure
- Experience with data visualization and presenting insights clearly
- Experience in fraud analytics, financial crime, or risk management models
- Knowledge of financial systems and data standards
- Experience with containerized model development using Kubernetes
- Exposure to banking or financial services
- Strong analytical, problem-solving, and communication skills
- Experience working in agile, multidisciplinary teams
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.
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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.
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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.
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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
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.
