Senior Data Scientist, Actimize

Overview

Senior Data Scientist on the NICE Actimize analytics team, building machine learning models and analytical solutions to detect and prevent fraud.

What you'll do

• 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.

What you'll need

• 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.
• 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.
• Experience troubleshooting production data and deployed models.
• Exposure to cloud platforms (AWS, Azure preferred).
• Experience with visualization and presenting insights clearly.

Nice to have

• 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.
• Kubernetes is a plus.

Details

• Location: Pune, India.
• Work mode: NiCE-FLEX hybrid model, 2 days working from the office and 3 days remote each week.
• Role type: Individual Contributor, reporting into Tech Manager, Actimize.
• Requisition ID: 11670.