Job Description

In this position, you’ll work closely with our marketing teams to help them find opportunities to drive the growth of new members and engagement of existing members across our channels. You will act as a data advocate and coach the wider business in our mission to become a truly data-driven company and drive tangible value through campaign-specific insights and a deep understanding of our member base. If you can help us to discover the information hidden in vast amounts of data, and make predictive models to deliver even better products, we'd love to hear from you. Your primary focus will be on applying machine learning techniques, doing statistical analysis, and building high-quality prediction systems integrated with our products. Role description: ● Interpret data, analyze results using statistical techniques and provide ongoing reports. ● Develop statistically significant experimentation frameworks to allow us to improve the targeting of our marketing through segmentation and assessing the incremental impact of campaigns. ● Create and develop predictive models using AI/ML technologies, installing and monitoring the production performance of models. ● Develop SQL and Python code to interrogate our data. ● Bring new ideas to the table relating to business questions, analytics approaches, datasets, and ways of working. ● Communicate analysis, relevant trends, and campaign performances (including SLAs & KPIs) to internal as well as external stakeholders and across the business. ● Drive technical innovation through active research and applications of new theories, techniques, and technologies. ● Stay on the cutting edge of industry-standard methodologies, trends, and new technologies. ● Locate and define new process improvement opportunities.

Requirements

● Minimum experience of 3 years in the role of a data scientist or data analyst. ● Knowledge and experience of the Python libraries especially with Pandas. ● Ability to effectively form relationships with the business in order to help with the adoption of data-driven decision-making. ● SQL knowledge and experience working with both relational and non-relational databases, query authoring as well as working familiarity with a variety of other databases and datasets. ● Familiarity with data modeling with tools and techniques such as SSAS, DAX, and Power BI.

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