A leading technology-enabled payments solutions company is looking to hire an experienced Data Scientist and Analytics Manager
- Lead and/or support the presentation of solutions to prospective clients
- Join client meetings and assist Business Development Manager with conceptualizing client requirements, the development of appropriate proof of concepts (POC), and use cases to illustrate the “art of the possible” to prospects and convert the analytical outputs into delivery reports or collateral with world-class storyboarding
- Assist as required in the Development of advanced predictive models across a range of outcomes (risk/Marketing etc.) using various techniques, to include, but not limited to Logistic/ Linear regression, Decision Trees and Machine Learning techniques
- Support Business Development Manager with producing power point presentations and proposals
- Help with the contracting process and ensuring that the solution or product is delivered to time, cost and quality quadrants based on the contract and the client’s expectations.
- Additionally, support the wider team Advisory and Information Services team as required with product development, pre-sales and sales support relating to analytical solutions, including client presentations, solution design, proposal development including costings and Letters of Engagement
- Seasoned data analyst or scientist ideally with experience of undertaking exploratory analysis and developing analytical solution in the card acquiring and/or consumer credit/charge card space, and across a number of disciplines/outcomes including risk, collections, marketing propensity, usage propensity etc. IS A MUST
- Able to translate the outputs of highly technical analysis into a form that can be understood by non-technical people.
- Practiced in the use of large data set, including transactional data, and ideally in the use of non-traditional data such as sentiment, social media etc
- In depth understanding of a high number of predictive model development approaches and techniques including both traditional (i.e., regression) and more emerging technologies (i.e. machine learning)
- Advanced user of a range of applicable software such as SAS, R, Statistica, Python, FICO model builder, Chaid, Answer Tree, Qlikview, Tableau etc.
- Highly presentable, confident, outgoing and articulate with experience of presenting to internal and external stakeholders, including clients
- Advanced PowerPoint skills is a must
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