Prodigy Finance - who we are
Prodigy Finance is a platform that enables financing for international postgraduate students at the world’s best universities, whilst delivering competitive financial and social returns to alumni, institutional and private investors.
This borderless and innovative model enables education loan financing to students from across the globe, whilst using predicted post-
degree affordability rather than present-day salary. Since 2007, Prodigy Finance has extended over US$500 million through the platform to fund over 12,000 students from over 130 countries.
Our team of over 160 (and growing) is already truly global. Our head office is in London with much of the team being based in beautiful Cape Town.
We also have an office in New York plus team members based across Europe and Asia.
We are funded by some of the best, pre-eminent institutions in the world including Index Ventures, Balderton Capital, RMIH, Credit Suisse and Deutsche Bank.
Why this is an amazing opportunity
This role is perfect for an experienced Data Scientist who wants to supercharge their career by experiencing first-hand what it is like to be part of an energetic, extremely fast-growing company.
The sense of impact and reward will be huge. You will help to build a product which makes a very real difference in the world.
Be a part of delivering socially responsible financial services to the masses; make it possible for students from more than 130 countries to obtain the finance to fulfil their dream of studying at the world’s top universities and schools.
We are a small non-hierarchical team; this means that you are going to get exposure to all aspects of our business immediately.
You’ll gain as much accountability as you can handle and have a huge influence on scaling the company.
Our team is very international and very sociable; you will interact with the broader business on a regular basis. The position will be based in Cape Town.
One of our goals is to build one of the top FinTech teams and cultures anywhere in the world. This means putting a lot of time into ensuring we only hire people with exceptional potential and creating the best working environment possible.
If you want to work somewhere where you're learning from some of the best brains in FinTech, this would be a good fit.
Why join Prodigy Finance
Be a part of a pioneering global growth company
Experience the excitement and learn from being part of an incredibly fast-growing young company. No kidding exponential growth. Happening right now
Be pivotal in scaling the business by identifying smart solutions and partners with tech at the heart of it
Enjoy the agility and flexibility offered by a startup culture. A sociable, relaxed and friendly work environment (with a serious coffee culture where you can wear shorts to work)
We will help you make your mark. Make a real impact on the business and experience a steep learning curve with huge opportunities to grow and develop
Gain an inside perspective on the functioning of a venture-backed FinTech startup, backed by top VCs, learn day-to-day management and build functional expertise
Build a platform that helps to make a very real difference in the world
What you will do in the role
As a Data Scientist, you will work in the Tech team alongside talented Software Engineers in order to build measurement and learning into the broader business products, processes and systems.
You will interact with people from all other teams and levels of seniority within Prodigy Finance as you go about your daily work.
Specific responsibilities will be to :
Collaborate with Product Owners, Software Engineers and Operations Managers to measure and improve the impact of their products, systems and processes
Look for relevant sources of data both inside and outside the business to enrich input to analysis and machine learning pipelines
Build automated measurement, learning and analysis pipelines for business products, systems and processes
Build automated visualisations
Educate Product Owners, Software Engineers and Operations Managers about the methods used by the Data Science team so that they can contribute to data-
based learning within the organisation
Document and explain the results of the Data Science team's work to others so that they can continue to apply and use these results in their daily work
What you will be measured on
The impact of what you learn and the systems you build
Your delivery of automated data science pipelines and visualisations
Your education of other teams and spreading of a culture of measurement and data-driven learning within the business
Your ability to think strategically but deliver change incrementally
What you need to be great at
Analytical thinking capability; be logical, systematic, strategic and pragmatic
Technical competence; love coding and look to continuously improve and find better ways of doing things
Strong attention to detail, both quantitative and qualitative, can organise large amounts of data from disparate sources
Able to learn new concepts and business issues quickly
Mindfulness; be considerate of the implications of your work, really care about what you are doing and the impact of your contribution
Problem-solving aptitude able to research complex open-ended problems and prepare solutions that address them and are backed by data and solid theoretical models
Ability to explain complex concepts to others with patience and humility
Biased towards action generate ideas, experiment with them, test them, learn from them, improve them, implement them, automate them
Collaborate well with colleagues of all levels of seniority
Excellent critical judgment; able to make good decisions, be trusted, respected and dependable, be proactive and responsive, ask the right questions, raise flags at the right time
Be accountable for the team’s outputs and targets. Able to multi-task and work in a high-pressured environment
Ability to educate and train team members to ensure they are aware of the methods used by the team. Also, able to identify gaps in training knowledge and close them when required
Who we are looking for; track record must haves
Experience working in a Data Scientist or related position, and working with data models in a production environment
A background in software development with Python and relevant Python libraries (e.g. NumPy, SciPy, scikit-learn, Pandas, TensorFlow)
A tertiary education that includes statistical methods and mathematics of data science (i.e. linear algebra and calculus)
Experience with one or more classic data science and machine learning algorithms and techniques (e.g. natural language processing, text mining, linear regression, classification, clustering, topic modelling, support vector machines)
Experience with relational databases or other tools for managing data
Experience translating customer needs into exciting data science projects
Experience that would be nice to have (but we’ll trade off if everything else fits)
Experience with using and deploying "big data" processing tools (e.g. Storm, Spark, Hadoop, MapReduce, Riak)
Experience with natural language processing models
Experience with neural networks and deep learning
Experience with transfer learning
Experience with anomaly detection
Experience with visualisation tools in production (e.g. d3)
Start-up experience. Sometimes the earth moves beneath your feet at Prodigy Finance, so you've got to be comfortable with ambiguity, able to wear lots of hats, and adapt easily as we continue to grow
The Prodigy Finance fit; attributes which run true in everyone at Team Prodigy
To be an A player at Prodigy Finance, you need to possess in spades - the following attributes :
Be curious enough to want to know more, think out the box, maybe even break the box, show initiative and be smart about it to find implementable, impactful solutions.
Push yourself to be better every day. Work with others across the world, be resilient, add value and then hold yourself accountable.
Encourage and celebrate each other.
Sense of humour survival. Bring energy and fun. Wear your heart on your sleeve. Work hard and find the time to play. We’re in this together.
Do you want to be our next Data Scientist? Here’s what to do now :
If this sounds exciting and you'd like to have an informal chat, get in touch below and tell us why you want to work at Prodigy Finance.
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