Data Scientist, VP

As a Data Scientist at the company, you will play a crucial role in leading, driving, and implementing the design and execution of data science tools and methods to leverage the data for driving customer solutions. You will be expected to bring together statistical, mathematical, machine learning, deep learning, generative AI, and software engineering skills to develop and deploy ethical models end-to-end. This position offers you the opportunity to sharpen your skills and create an impact by applying a software engineering and product development perspective to solve complex business challenges. **Key Responsibilities:** - Work closely with business stakeholders to define detailed business questions, problems, or opportunities that can be addressed through advanced analytics - Understand the complex requirements and needs of business stakeholders, develop strong relationships, form hypotheses, and identify suitable data and analytics solutions to meet those needs and align with the business strategy - Articulate advanced data and analytics opportunities, visualize them through data visualization for stakeholder engagement, and ensure understanding of benefits, trade-offs, and ethics - Lead multi-disciplinary data and analytics teams in an agile manner to achieve project outcomes - Select, build, train, and test complex machine learning models, considering model validation, performance monitoring, risk, governance, and ethics - Lead stakeholder engagement activities, ensuring stakeholder needs and concerns are identified and addressed - Identify opportunities to leverage data science expertise for external customers aligned with the Group strategy - Explore data, ensuring proper usage of golden source data, and establish best practices for machine learning, deep learning, or Gen AI development **Qualifications Required:** - Academic background in a STEM discipline such as Mathematics, Physics, Engineering, or Computer Science - Minimum of twelve years of experience in statistical modeling, machine learning, deep learning, and Gen AI techniques - Proficiency in programming languages and software engineering fundamentals - Good financial services knowledge and the ability to identify wider business impact, risks, and opportunities - Ability to use data to solve business problems from hypotheses to resolution - Experience in synthesizing, translating, and visualizing data and insights for key stakeholders - Leadership and coaching experience, along with knowledge of Cloud applications - Excellent communication skills with the ability to engage and manage a wide range of stakeholders,