Job title : Sr Data Scientist: Digital Growth Job Location : Western Cape, Cape Town Deadline : December 15, 2024 Quick Recommended Links Jobs by Location Job by industries About the role As a data scientist your work is a canvas for change, painted with the data you explore and the insights you uncover.
You're not just joining a team; you're embarking on a mission to reshape the financial landscape for all Africans, making tomorrow not just different, but better.
Turning data into pathways, obstacles into stepping stones, and potential into reality.
Together, we can build lasting financial confidence across Africa, one insight at a time.
This is a data science role focusing on acquiring as many quality clients as possible through digital marketing, in the most cost efficient way possible. What you'll achieve in the first 12 months?
We have all the data we need to understand, measure and influence client acquisition.
Work across the end-to-end client acquisition journey, from off platform to product conversion, to ensure data is created and consumed in a way that enables you to bring them together to fuel your insights and modelling.
Ensure data quality and interoperability is owned at source by working with engineers, architects, and marketers across the ecosystem.
Success will be measured by the completeness and quality of data, facilitating a comprehensive view of the client acquisition journey.
We can reliably and predictably attract the targeted segments of the market onto our platform: Collaborate with campaign managers to iterate on marketing campaigns, refine our segments and establish the most cost-effective way to bring prospective clients to our website to evaluate our products.
Produce insights, run experiments, and develop predictive models to optimise channel specific campaign performance and cross channel spend.
E.g.
What budget and channel allocations do we need to hit our client acquisition and cost of acquisition targets for segment X next quarter?
Success will be measured in the number of quality clients acquired through each campaign and efficiency of the spend on it (e.g.
client LTV / CAC, campaign ROI).
Prospective clients have all the relevant information and advice they need to understand their needs and build confidence in our products: Work closely with UX designers and user researchers to create the best landing and evaluation journey experience for prospective clients, optimising content and journey's that are best suited for each segment.
Involve user researchers to uncover the why behind the what.
E.g.
Which web pages contribute most to an acquisition?
Do people prefer handholding through our Call Centre Agents or directing their own journey through long form web pages?
Success will be measured by conversion of on-platform prospects who enter the qualification funnel and through qualitative surveys about their confidence and experience. Once a client decides, the rest of the product onboarding process is so transparent and frictionless, there's almost no drop off: Work with product houses to identify points in the product application and onboarding journey that cause drop off.
Work with user researchers to optimise for maintaining transparency and confidence, while addressing any accessibility needs.
E.g.
Which parts of the onboarding process require the longest time, how can data and ML be used to reduce or even eliminate it?
Success will be measured in completion times and rates in this final step of the process. As a team, we always know how well we're performing and (roughly) why: Create datasets, metric frameworks and visualisations that together provide information-rich stories about our activities and their performance.
These stories should cover everything from the digital marketing channels and partners we're using, to the format and nature of the content (e.g.
video vs image, animal photos vs people photos).
Leverage computer vision and/or NLP as a service to enrich your data to support this content rich analysis.
Success will be measured in the depth of understanding, and minutes it takes, for the team to learn about their key metrics and drivers. Qualification and Experience Degree or Diploma with 4 to 6 years related experience.
Research / Data Analysis jobs