Data Scientist Job Opening in Cape Town Feb 2024
Data Scientist Job – Recruit Digital in Cape Town Feb 2024
Remuneration: | R30000 – R50000 per month Cost to company |
Location: | Cape Town |
Type: | Permanent |
Reference: | #868 |
One of the Cape Town’s leading fintech startups, enabling small businesses to quickly and easily accept card payments at their store, is looking for a data scientist to join their team.
Having had a successful launch and built a base of happy merchants – leading to a significant quantity of new business. With this growing availability of data, we are at the stage where analysis of this data is beginning to become possible with significant sample size.
This is a project based role relying on a combination of programming, analytical, statistical and problem-solving skills to:
- Manipulate and organise large data sets using a combination of programming skills (e.g. SQL) and collaboration with other members of the product & data teams
- Collaborate with the relevant domain team (sales, business development, growth, etc) to conclude meaningful results and recommendations from these datasets using analytical tools and frameworks (e.g. using R/Python and statistical and machine learning techniques to create reports/dashboards/tools)
- Support with the implementation of recommendations to drive business value and measure results and effectiveness
Our mission is to bring delight back into commerce. Our first product is a mobile card reader and point-of-sale application that make it possible for any business to accept card payments at their store or on the go, simply using their smartphone or tablet.
Role – what will you be doing?
You will be a part of our data and risk team working closely with our technical product team as well as other domain focused teams. You will be conducting thorough analyses to solve challenging problems that lead to meaningful business value. The problems segment into two broad categories: (1) retrospective and (2) predicative.
Retrospective problems
- You will be examining current business process by evaluating the data generated, identifying issues and proposing solutions to increase efficiencies, enhance scaling capabilities and educate domain teams around the implications of their current actions. This will be done through a series of hypothesis generation, testing and validation in combination with management and domain teams.
Predicative problems
These problem types require all of the steps for retrospective problems, with additional complexity. You will also need to be able to:
- Test for causation rather than simply correlation
- Use statistical and machine learning models to forecast future outcomes
- Continuously conduct experience studies to determine if models remain relevant and iterate for cases when models are no longer statistically significant
Key requirements:
- Knowledge and experience with SQL and R/Python
- Strong systems thinker – the ability to understand and simplify complex and interlinked systems
- Creative problem solver
- Attention to detail
Bonus points
- Experience in the financial services industry
- Experience with JavaScript
- Interest/experience in machine learning implementation
- Interest/experience in big data implementation
Expectations
Dealing with business
- Preventing and solving problems: diagnostic information gathering and research, analytical thinking, application of conceptual thinking to the problem.
Achieving results:
- Proactive/ initiative, customer orientated, fostering innovation, continuous improvement mind-set, appreciation of results, business acumen, thoroughness and detail oriented.
Dealing with self-management
- You will be given the independence that you need to execute tasks in your own way – you should be someone that thrives in this environment.
Value proposition – what will you be getting?
As a member of the team, we are offering:
- Valuable learning opportunities from seasoned professionals with an entrepreneurial spirit.
- Insight into the running’s of a high growth, innovative start-up.
- Competitive remuneration