The Senior Data Scientist will lead the design, development, and deployment of complex AI and machine learning models to solve strategic business problems within the financial sector. This role requires deep expertise in data science methodologies, advanced proficiency in relevant tools and technologies, and the ability to independently translate complex business needs into scalable and impactful analytical solutions. The Senior Data Scientist will mentor junior team members, contribute to technical strategy, and communicate findings to executive stakeholders.
Focus: Project leadership, strategic analysis, and advanced model development.
The difference you will make:
- Lead end-to-end data science projects from conception to deployment.
- Develop and implement advanced machine learning models and algorithms in banking applications.
- Conduct strategic data analysis to inform business decisions and identify new opportunities.
- Communicate complex technical findings to senior management and stakeholders.
- Drive innovation in data science methodologies and tools.
Education: Bachelor's degree in Data Science, Economics, Computer Science, Engineering, Statistics, Mathematics, Physics, Operations Research, or a related discipline with an outstanding academic record; Master's or Ph.D. preferred.
Experience:
- 5+ years of progressive experience as a Data Scientist, with a strong and demonstrable track record of independently leading and delivering successful, complex data-driven solutions with significant business impact.
- Extensive experience in the financial services industry, with a deep understanding of financial data and business processes.
- Significant experience with specific AI applications in finance (e.g., fraud detection, risk management, algorithmic trading, customer analytics) and a proven ability to drive tangible results.
Technical Skills:
- Mastery in at least two of the following languages: Python, Java, Scala, and/or R, with expertise in relevant libraries and frameworks.
- Deep expertise in a wide range of machine learning frameworks (TensorFlow, PyTorch, scikit-learn, and potentially more specialized libraries).
- Comprehensive and in-depth understanding of foundational and advanced statistics concepts and ML algorithms, including deep learning architectures and specialized techniques. o Familiarity with generative AI tools (e.g., Hugging Face, LangChain)
- Advanced mathematical skills, including a strong theoretical understanding and practical application of relevant mathematical concepts.
- Expert-level proficiency in SQL and various database management systems (e.g., SQL Server, PostgreSQL, NoSQL databases).
- Extensive experience with advanced data visualization tools (e.g., Tableau, Power BI) and the ability to create impactful and insightful dashboards.
- Significant experience with cloud computing platforms (AWS, Azure, GCP) and their AI/ML services.
- Proven experience in architecting and working on large, complex data sets, with deep expertise in Hadoop, Spark, and related big data technologies.
- Expertise with various distributed databases such as Hive, Impala, Redis, etc., and the ability to design and optimize data storage solutions.
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
