nice · India - Pune
Skills: Python, SQL, AWS, Docker
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: Analyzing large volumes of client data to extract actionable insights, assess AML compliance and identify and flag inconsistencies or potential compliance risks. 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 datasets. Utilize statistical techniques and quantitative analysis to identify trends, patterns, and correlations within the data. Translate business problems into analytical solutions in partnership with Product, Engineering, and domain SMEs. Stay abreast of the latest advancements in Data Science, Machine Learning, Generative AI and recommend innovative approaches to solve business challenges. Proficiency in handling imperfections in data is an imp …tr…
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