The Principal Data Scientist will provide strategic technical leadership and direction for data science initiatives across the organization, particularly within the financial sector. This role is responsible for driving innovation, setting technical standards, mentoring a team of data scientists, and collaborating with senior stakeholders to define and deliver high-impact AI and machine learning solutions that align with business strategy and drive significant value.
The difference you will make
- Define the technical data science strategy and roadmap.
- Lead the research and development of cutting-edge AI solutions.
- Evaluate and implement new data science technologies and platforms.
- Provide technical leadership and guidance to the data science team.
- Ensure the scalability and reliability of data science infrastructure.
Education
- Master's degree or Ph.D. in Data Science, Statistics, Mathematics, Computer Science, Engineering, or a related quantitative field with an exceptional academic record
Experience:
- 8+ years of progressive experience in data science, with more than 2 years spent leading and successfully delivering complex AI/ML projects with demonstrable business impact
- Extensive and deep experience in the financial services industry, with a comprehensive understanding of financial data, regulations, and business challenges
- Proven experience in leading and mentoring data science teams
- A strong portfolio showcasing the successful application of AI/ML to solve significant financial problems (e.g., transformative fraud prevention systems, advanced risk management platforms, high-impact algorithmic trading strategies, game-changing customer analytics solutions)
Technical Skills:
- Expert-level mastery in multiple programming languages relevant to data science (e.g., Python, R, Scala, Java) and their associated libraries and frameworks.
- Deep and comprehensive expertise across a wide range of machine learning frameworks, including advanced knowledge of deep learning architectures and specialized tools.
- Exceptional understanding of both foundational and cutting-edge statistical concepts and ML algorithms, including deep learning architecture and specialized tools.
- Deep understanding of Data and AI governance frameworks and requirements.
- Advanced mathematical skills, demonstrating a strong theoretical understanding and practical application to complex financial problems.
- Expert-level proficiency in SQL and a variety of database management systems (both relational and NoSQL), with the ability to design and optimize data storage and retrieval for large-scale AI/ML applications.
- Extensive experience with advanced data visualization tools and the ability to communicate complex insights to executive audiences through compelling visuals and narratives.
- Deep and practical experience with cloud computing platforms (AWS, Azure, GCP) and their comprehensive suite of AI/ML services, including architecting and deploying scalable solutions.
- Proven expertise in designing and working with large, complex data sets and big data technologies (Hadoop, Spark, etc.), including the ability to optimize data processing workflows for performance and scalability.
- Mastery of various distributed databases (Hive, Impala, Redis, etc.) and a proven ability to design and implement efficient data storage and access patterns for AI/ML workloads.
Soft Skills
- Strong ownership and accountability for assigned work.
- Clear and professional verbal and written communication.
- Effective time management and task prioritization.
- Analytical thinking and problem-solving skills.
- Ability to work independently, collaborate effectively and mentor junior team members.
- Ability to actively listen to customers and accurately understand their needs, expectations, and challenges.
- Adaptability and learning agility in a fast-paced environment.
- Strong attention to detail and a commitment to quality.
- Receptiveness to feedback and continuous improvement mindset.
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