Company Description:Actimize Premier is seeking a Data Scientist to design, develop, and optimize cutting-edge algorithms and machine learning solutions for financial fraud prevention and anti-money laundering (AML) applications. You will work on behavioral analytics and machine learning models while mentoring junior team members and collaborating closely with cross-functional teams. This role provides an opportunity to contribute to innovative, impactful products at the forefront of financial crime prevention technology.Job Description:Develop and optimize advanced machine learning models and algorithms for fraud detection and AML applications.Mentor and guide junior data scientists and analysts, fostering a collaborative and high-performance team environment.Leverage cloud platforms (AWS, Azure, Google Cloud) to implement scalable AI/ML solutions.Contribute to the design and implementation of core algorithms, mathematical models, and data-driven solutions.Explore and apply emerging technologies such as Generative AI to enhance fraud detection capabilities.Collaborate with product managers, engineers, and other stakeholders to translate business requirements into robust technical solutions.Perform statistical analysis, data mining, and visualization using tools like Python or R.Drive innovation by researching and integrating the latest advancements in data science and machine learning.Support the team in building user behavior models, leveraging Bayesian statistics, and exploring advanced techniques like social network analysis.Qualifications:Proficiency in Python for statistical analysis, data modeling, and visualization.Experience with cloud technologies and platforms (AWS, Azure, or Google Cloud).Solid understanding of databases and SQL (e.g., MySQL).Exposure to generative AI techniques and their applications in data science.Additional Information:Knowledge of user behavior modeling and Bayesian statistics.Experience in natural language processing (NLP).Familiarity with tools and libraries for generative AI (e.g., Transformer models).Understanding of the financial crime prevention domain and its associated challenges. #J-18808-Ljbffr