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Python Data Science Consultant
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**Mission**
Support the Asset Liability Management and Financial Structuring team (“ALM”) in enhancing the quality and efficiency of their internally developed data analytics framework.
Furthermore, the team is looking to improve their development and documentation code capabilities to higher professional standards and best practices.
- Code Review and Refactoring: Analyse the existing Python code, understand its business logic and objectives, and support the team to refactor it with professional knowledge to improve maintainability, performance, readability, and adherence to best practices as implemented by code quality gate. Ensuring that developed code is aligned with financial industry standards and best practices
- New Code Development: Develop new Python code for additional topics and integrate it seamlessly with existing developments and systems to maintain consistency and to facilitate future expansions
- Database Development and Integration: Develop and support new database schemas in Microsoft SQL Server and associated data loading scripts, integrating the database with the IT infrastructure to streamline data storage and management
- Test: Write unit tests to fulfil the required code coverage quality gates, prepare and participate in system/integration tests and user acceptance tests
- Documentation: Create comprehensive, business-friendly documentation for all developed code to ensure that the team members can understand and maintain the code effectively
- Training and Support: Provide training and support to the team members in the areas of advanced coding, database development and integration, and IT infrastructure management, empowering them to grow their skill set and contribute more effectively to future projects
**Deliverables**
- Requirements and design documents, following the structure and formats approved by ALM
- Source code fulfilling the client’s quality gate requirements, configuration, and automated unit tests (pytest), checked in to the provided versioning system (Git), along with documentation (e.g., docstring and Markdown)
- System/Integration test results, following the structure and formats approved by ALM
- Operator and end-user documentation
**Technical skills**
Mandatory
- Bachelor's degree in information technology, Mathematics, Physics, or similar field, and/or equivalent professional experience
- Minimum of 6 years’ experience in data science with Python and SQL in a professional environment
- Object-Oriented Programming: Strong skills in object-oriented programming, enabling the creation of modular, reusable, and maintainable code that adheres to modern programming paradigms
- Experience with automated Python testing, e.g., unit-test, pytest
- Proficient knowledge of and experience with the following Python libraries: NumPy, Pandas
- Experience with the use of the Git version control systems
Desired
- Experience in financial data modelling, financial risk concepts, financial derivatives, and risk management techniques
- Proficient knowledge of and experience with the following Python libraries: Seaborn, SciPy, Statsmodels, Scikit-learn, PyTorch, Plotly, Dash, Matplotlib and Streamlit
- Good understanding of and experience with: XML, JSON, YAML
- Experience with continuous integration and continues delivery pipelines, e.g., Jenkins
- Experience with Enterprise Data Warehouse development
- Experience with specialized reporting solutions such as, e.g., Tableau, PowerBI
- Good understanding of a cloud-based microservice architecture
- Experience with documentation of business requirements and with technical writing
- Experience with agile methodologies, e.g., Scrum
- Experience with AI-assisted programming tools, e.g., Github CoPilot, ChatGPT
- Experience with MS Excel
**Soft-skills**
- Excellent English communication and presentation skills, ensuring clear and concise communication with the team members and fostering a smooth and effective collaboration process
- Proven customer-oriented change management communication skills
