Senior Data Scientist, Actimize (Machine Learning)

About this role

Not quite right? These jobs in Pune match the same skills — apply to a few to improve your chances.

Role: Sales Intern

12thwonder

In OfficePune12K/mo

Apply

CLOUD MACHINE LEARNING ENGINEER (AWS)

Vodafone Intelligent Solutions (VOIS)

In OfficePune

Apply

Specialist Cloud Database Engineer (SQL, DevOps, AWS)

NICE

In OfficePune

Apply

Software Engineer II

Xplor

In OfficePune

Apply

Skills you'll use

What you'll do

• 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.

Who can apply

• 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).

About NICE

Searching for “NICE jobs” or “jobs at NICE”? You’re in the right place.