Data Scientist/ML Engineer

Job Summary: As a Data Scientist in the banking domain, you will be responsible for analyzing complex data sets to provide actionable insights that drive strategic decision-making. You will collaborate with cross-functional teams to develop predictive models, enhance risk management strategies, and improve customer segmentation and targeting. Key Responsibilities: Analyze large volumes of structured and unstructured data to identify trends, patterns, and anomalies. Develop and implement predictive models to enhance customer acquisition, retention, and risk assessment. Collaborate with stakeholders to define business problems and translate them into analytical solutions. Create data visualizations and dashboards to communicate findings effectively to non-technical audiences. Conduct A/B testing and experimentation to optimize marketing strategies and product offerings. Stay updated on industry trends and advancements in data science and banking technologies. Work with data engineering teams to ensure data quality and integrity. Qualifications: Bachelor's or Master's degree in Data Science, Statistics, Computer Science, Mathematics, or a related field. 2 to 10 years of experience in data science, preferably within the banking or financial services industry. Proficiency in programming languages such as Python, R, or SQL. Experience with machine learning frameworks (e.g., TensorFlow, Scikit-learn) and statistical analysis tools. Strong understanding of data visualization tools (e.g., Tableau, Power BI, or similar). Knowledge of banking regulations and compliance standards is a plus. Excellent problem-solving skills and the ability to work in a fast-paced environment. Strong communication skills, with the ability to present complex data insights to diverse audiences. #J-18808-Ljbffr