What do we offer?We offer both remote and hybrid work opportunitiesIntellinexus is an SME, therefore you get a lot of exposure to different technologies, solutions and techniques during projects.Intellinexus supports career development and growth of its employees, therefore time and money is invested to grow their consultants in their careers.Overall purpose of the roleThis is a data science role focusing on acquiring as many quality clients as possible through performance and brand 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.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.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.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.Duties & ResponsibilitiesData Scientists are the people who bring practices from empirical science to life to drive the iterative product development lifecycle. They embed within teams they support, achieving a marriage of minds with their stakeholders and an integration of objectives and workflows.This is a role where mastery in data wrangling, metric setting, experimentation, machine learning and data storytelling are combined to enable product teams to become learning machines.Examples of things a data scientist does while embedded in their commercial team:Driving data creation: Establish the first principles and facilitate discussions about how to create data about relevant user behaviours and measure success.Wrangling data autonomously: Wrangle data into the ideal format for the necessary tool.Setting team metrics: Define holistic measurement frameworks that enable the team to explore their performance holistically.Producing insights: Identity loosely defined commercial problems and produce meaningful insights that guide iterations of the teams products and go-to-market campaigns.Developing ML models: Structure commercial problems into prediction problems by clarifying both what is being predicted and how that enables us to change our products or campaigns.Carrying out controlled experiments: Establish the learning goals of their team, crafting hypothesis statements and learning roadmap wherever needed.Segmenting the client base: Using rule and unsupervised learning-based approaches to segment the client base.Creating impactful visualisations: Produce data and interactive visualisations that enable the whole team to address their recurring reporting and insight needs.Partnering for impact: Partner with stakeholders to make sure they gain the confidence they need to drive changes in the product roadmap.Evolving the learning mindset of the team: Create a culture of insights and learning, where everyone obsesses about their success metrics.Interested?Our aim is to help you build a successful career with usWe're all about building strong, lasting relationships with our employees. We know that you have hopes for your future – your career, your personal development, and for achieving great things.
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