Senior Data Scientist

3 weeks ago

Cape Town, South Africa Verve Global Recruitment (Pty) Ltd Full time

**JOB PROFILE: Senior Data Scientist**

**1. LOCATION**

**Stellenbosch - hybrid ( 3 days per week at office )**

**2. PURPOSE STATEMENT**
- To assist in building and delivering the AI strategy to ensure the bank is able to compete in a fast changing landscape where data science is a key future-oriented strategic differentiator.
- To help automate and improve processes through data science, and create new products and services, and assist with improved decision making based on data.
- To design and implement machine learning models to better understand the drivers of business performance and enable improved management decision-making.

**3. DIRECT REPORTS**

The job holder has no direct reports, however you will coach junior Data Scientists and upskill less experienced
D ata Scientists in the function. Drive specialist skills and strategic AI direction within the team.

**4. KEY PERFORMANCE AREAS**

**4.1** **Ownership and responsibility of delivery.**

**4.2** **Documentation and prioritisation of business requirement.**
**4.3** **Build machine learning models and AI solutions.**

**4.4** **Interaction and engagement with team.**

**4.5** **Research and continuous improvement.**

**5. KEY TASKS & ACCOUNTABILITIES**

**5.1** **Ownership and responsibility of delivery.**
- Adhere to formal data science process and ensuring best practices are applied in each project:

- Knowledgeable of the relevant environment in which they will work.
- Display interest in understanding the allocated client area: ask relevant questions.
- Effectively and efficiently addressing client queries / questions.
- Ask relevant questions to ensure understanding of the core business need driving the specific request.
- Review and check integrity of existing machine learning (ML) models or analysis affecting within business area and conduct maintenance to ensure relevance.
- Escalate serious issues to Lead or Product Manager where required.
- Interact with business users on a business level to understand the potential risk / business impact of need.

**5.2** **Documentation and prioritisation of business requirement.**
- Accurately document the business requirement using the formal Data Science ideation templates, such as business requirements gathering, solution design, model experimental design and validation, System

Development Lifecycle (SDLC) process and Quality Assurance (QA) checks as well as monitoring when going to production.

1 | P a g e

**JOB PROFILE. Data Scientist III.**
- Documentation needs to adhere to data science life cycle (DSLC) and meet formal regulatory and internal risk and compliance standards as set out by Model Risk Management (MRM).
- Serve on the Data Science Forum / Community of Practice: Data Science.
- Translate business needs into technical/system requirements applicable to IT and various other technically focused departments to ensure machine learning models can be implemented.
- Complete solution design within required context, e.g. delivering models as micro services.
- Collaborate with business owner to differentiate and prioritise work according to value that it will add on a company level.
- Communicate project priorities to clients and team members to:

- Ensure effective management of client expectations, and
- Ensure the accurate allocation of the team’s capacity.
- Prepare formal communication / feedback to stakeholders on developed reports, analysis or models in an understandable format.

**5.3** **Build machine learning models and AI solutions.**
- Develop most appropriate machine learning model based on specific business need.
- Design / develop and implement machine learning models or solutions within business.
- Monitor continuous relevance, predictive strength and stability within business.
- Conduct development in line with prescribed data science lifecycle.
- Extend knowledge base and development of new statistical/machine learning methods to improve business positioning within machine learning and AI.
- Assist in delivering the AI strategy and business objectives.
- Identify opportunities where new techniques and tools can be used to disrupt the bank from within.

**5.4** **Interaction and engagement with team.**
- Adhere to principles of data science team to ideate and build a supportive and collaborative culture.
- Adhere to agreed housekeeping principles on internal folders, repositories, databases, models and deployment thereof.
- Adhere to Data Science life cycle and best practices to ensure continuity in all tasks.
- Assist with the establishment of processes to ensure effective resolution of relevant problem statements.
- Actively participate in and ensure occurrence of knowledge sharing and regularly test / share ideas with team members.
- Internal and external code reviews and models evaluation.
- Collaborate and assist with machine learning model design sessions to ensure best practices are adhered to.
- Take and accept final ownership for the building of code, variables

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