D&T Associate Manager - Data Science

As an Associate Manager Data Science within the Digital and Technology team, you will play a crucial role in modeling complex problems, uncovering insights, and streamlining workflows by utilizing statistical analysis, machine learning, generative AI, and data visualization techniques with cutting-edge big data & AI technologies. Your primary focus will involve collaborating with business partners to develop data science projects that drive advanced analytics and AI adoption to gain a competitive edge, enhance operational efficiency, and foster innovation. Your responsibilities will include executing end-to-end advanced data science projects aligned with business goals, mastering on-premise and cloud-based data warehousing and data lakes, staying abreast of the latest AI and ML technologies, constructing data pipelines for data ingestion, cleaning and imputing unclean data, conducting in-depth exploratory data analysis, engineering features relevant to data science problems, creating and assessing data models using various techniques, and presenting modeling results and recommendations to stakeholders in a clear and actionable manner. Moreover, you will collaborate closely with business stakeholders to identify challenges and opportunities, develop data-driven strategies, and implement solutions leveraging AI and machine learning technologies. It is essential to adhere to established standards, enhance documentation, share knowledge within teams, ensure data accuracy, consistency, and security, and effectively collaborate with team members. To qualify for this role, you should possess a Bachelor's or Master's degree in Computer Science, Engineering, Statistics, or Applied Mathematics, along with at least 4 years of experience in data science. You should have a strong background in machine learning, statistical analysis, and predictive modeling, with practical expertise in programming languages like Python, R, or Scala. Proficiency in big data technologies, cloud-based solutions, and experience in developing scalable machine learning models for production environments are crucial. Additionally, familiarity with data engineering tools, cloud services platforms, containerization, CI/CD tools, and excellent communication skills are required for this position. As an integral part of a fast-paced and collaborative environment, you should demonstrate strong analytical skills, problem-solving abilities, and have a growth mindset to drive innovation. Your leadership behaviors should emphasize building outstanding teams, setting clear directions, simplification, collaboration, execution, accountability, fostering growth, embracing inclusivity, and maintaining an external focus to excel in this role.,