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Lynx Financial Crime Tech S.A., We are an AI-driven software company specializing in detecting and predicting behavioral patterns. Led by industry experts and academics, we develop and implement cutting-edge, self-learning AI technologies. Our platform excels in low latency transaction processing technologies and is available both on-premise and on the cloud. We prioritize VISION, AGILITY, and SPEED to provide outstanding customer experiences and have built long-lasting, trustworthy relationships with some of the top financial institutions, fintechs, and commercial enterprises worldwide. We embrace a strong risk culture and all of our professionals at all levels are expected to take a proactive and responsible approach toward risk management. Our mission is to contribute to help more people and businesses prosper. We embrace a strong risk culture and all our professionals at all levels are expected to take a proactive and responsible approach toward risk management. Lynx is proud of being an organization where there are equal opportunities regardless of age, gender, disability, civil status, race, religion or sexual orientation We are seeking a technically proficient Junior Data Scientist to join our analytics team. This role focuses on data processing, modeling, and visualization to extract valuable insights that guide strategic decision-making. Responsibilities: Collect, clean, and transform data from multiple sources using ETL (Extract, Transform, Load) tools. Apply statistical techniques and machine learning methods for exploratory and predictive analysis. Develop predictive models using Python or R and evaluate their performance with appropriate metrics. Generate interactive visualizations and reports using libraries such as Matplotlib, Seaborn, or BI tools (Tableau, Power BI). Collaborate with cross-functional teams to implement data-driven solutions. Requirements: Bachelor's degree in Data Science, Statistics, Mathematics, Computer Science, or related fields. Practical knowledge of programming languages such as Python or R, as well as data analysis libraries (Pandas, NumPy). Familiarity with machine learning algorithms and statistical modeling techniques. Strong analytical skills and the ability to communicate technical results effectively. #J-18808-Ljbffr
