Senior Manager Data Scientist - Banking Domain

As a highly experienced Mid-Senior Level Data Scientist with 10-15 years of experience in the banking sector, you will be responsible for leading strategic data analysis initiatives to generate critical insights and trends. Your expertise in developing and deploying advanced predictive models using statistical and machine learning techniques will drive business outcomes and innovation. Additionally, you will be instrumental in implementing data governance frameworks, evaluating cutting-edge technologies, and fostering cross-functional collaboration to align data-driven strategies with organizational goals. Your key responsibilities will include: - Leading strategic data analysis projects on large datasets to identify trends and anomalies crucial for banking operations. - Designing, developing, and deploying advanced predictive models to enhance business outcomes and drive innovation. - Developing and implementing data governance frameworks to ensure data quality, integrity, and compliance with regulatory standards. - Evaluating and implementing innovative technologies to improve data analytics capabilities and support business growth. - Collaborating with various departments to execute data-driven strategies and initiatives. - Mentoring and guiding junior data scientists and analysts to foster continuous learning and innovation. - Preparing and delivering detailed reports and presentations to senior management and stakeholders. - Keeping abreast of industry trends and emerging technologies to enhance analytical capabilities and drive business value. The qualifications required for this role include: - A Bachelor's degree in Data Science, Computer Science, Statistics, Mathematics, or a related field; a Master's or PhD degree is preferred. - 10-15 years of hands-on experience in data science, with a significant portion in the banking or financial services industry. - Proficiency in programming languages such as Python, R, or SQL, and experience with data visualization tools like Tableau, Power BI, or Matplotlib. - Expertise in machine learning frameworks and libraries such as scikit-learn, TensorFlow, or PyTorch. - Strong understanding of database management systems, data warehousing solutions, and big data technologies. - Superior analytical and problem-solving skills with the ability to interpret complex data and draw actionable insights. - Exceptional written and verbal communication skills to effectively present technical information to non-technical stakeholders and executive leadership. Preferred qualifications for this role include comprehensive domain knowledge of banking processes, relevant certifications, project management experience, and strong soft skills such as strategic thinking and attention to detail.,