Senior Data Scientist

Responsibilities

• Lead and mentor a team of data scientists/analysts.

• Provide analytical insights by analysing various types of data, including mining our customer data, reviewing relevant cases/samples, and incorporating feedback from others.

• Work closely with business partners and stakeholders to determine how to design analysis, testing, and measurement approaches that will significantly improve our ability to understand and address emerging business issues.

• Produce intelligent, scalable, and automated solutions by leveraging data science skills.

• Work closely with technology teams on the development of new capabilities to define requirements and priorities based on data analysis and business knowledge.

• Developing expertise in specific areas by leading analytical projects independently, while setting goals, providing benefit estimations, defining workflows, and coordinating timelines in advance.

• Providing updates to leadership, peers and other stakeholders that will simplify and clarify complex concepts and the results of analyses effectively, with emphasis on the actionable outcomes and impact on business.

Requirements

• 4+ years in advanced analytics, statistical modelling, and machine learning.

• Best practice knowledge in credit risk - a strong understanding of the full lifecycle from origination to debt collection.

• Well-versed with ML algos, BIG data concepts, and cloud implementations.

• High proficiency in Python and SQL/NoSQL.

• Collections and digital channel experience are a plus.

• Strong organizational skills and excellent follow-through.

• Outstanding written, verbal, and interpersonal communication skills.

• High emotional intelligence, a can-do mentality and a creative approach to problem-solving.

• Takes personal ownership, self-starter - ability to drive projects with minimal guidance and focus on high-impact work.

• Learns continuously; seeks out knowledge, ideas, and feedback.

• Looks for opportunities to build their own skills, knowledge, and expertise.

• Experience with big data and cloud computing, viz., Spark, Hadoop (MapReduce, Pig, Hive).

• Experience in risk and credit score domains preferred.