Data Scientist
Skills
About This Role
Overview
The Data Scientist works with business executives and various departments to deliver advanced data science solutions for implementation.
Use cases include, but are not limited to, intelligent character recognition, computer vision, behavioral analyses, early warning sign analyses, generative artificial intelligence, natural language processing (NLP), large language models (LLMs), and hyper-personalisation.
The role involves designing, testing, and launching innovative and complex analytical models using a combination of contemporary and traditional data mining techniques applied to both structured and unstructured datasets.
The Data Scientist also contributes to the development of big data capabilities and coordinates cross-functional analytical initiatives across the company.
Key Accountabilities
- Provide advanced data science solutions in collaboration with business executives and multiple departments.
- Design, test, and deploy innovative analytical and AI models
- Apply data mining techniques to structured and unstructured datasets
- Support the development and utilization of big data capabilities
- Coordinate cross-functional analytics initiatives
- Work on data mining and collection procedures
- Ensure data quality and integrity
- Interpret and analyze data problems
- Conceive, plan, and prioritize data projects
- Build analytical systems, predictive models, and artificial intelligence capabilities
- Test the performance of data-driven products
- Visualize data and create innovative reports
- Present insights to key stakeholders.
- Experiment with new models and techniques
Requirements
- Qualification as a Data Scientist
- Solid understanding of machine learning
- Knowledge of data management, advanced analytics, and visualization techniques
- Strong aptitude for statistical analysis and predictive modelling
- Experience with Artificial Intelligence
- Good knowledge of R, Python, and MATLAB
- Experience with SQL and NoSQL databases
- Excellent oral and written communication and presentation skills
- Strong business mindset and advanced mathematics skills
- Exceptional interpersonal and inclusive people skills
- Commitment to ongoing professional development and company values
- Strong strategic thinking and problem-framing abilities
- Solid understanding of IT system architecture
Additional / Preferred Experience
- Experience with modern data quality management tools in the context of data quality and governance
- Familiarity with automated data quality management, data sharing, data traceability for business intelligence, and data warehouse re-engineering
- Experience in the Financial Services industry.
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