Senior Data Scientist, Actimize (Machine Learning)

• 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
• 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.