Data Science Manager

Job Purpose - The overall goal is to find innovative ways to identify / understand / profile target audiences and uncover patterns/correlations that can be acted upon to drive the business. Key Result Areas/ Responsibilities - Identify key business questions, generate and validate hypotheses to uncover insights through data source exploration, visualization, and prediction techniques - Develop, optimize and evaluate model(s) that translate business questions in an iterative way - Explore large datasets (internal and external sources) to find patterns and relationship - Draw inferences and conclusions; frame decision recommendations in a way that is consistent with model results - Communicate results in a clear, concise and compelling manner. * - Ability and know how to deal with imperfections in data - Maintain large data sets from multiple sources: merge files, restructure and recode variables, assign labels and values, check for errors, etc. - Manage data: inspect, clean and transform data. - Run database queries and provide insights where required to various departments. * - Work collaboratively with various commercial stakeholders (such as Marketing, Digital Marketing Specialist, Web Analyst, CRM Specialist, Social Media Specialist, Sales, etc) to glean information on brand, sales and customer data (via data management platforms, web, social media analytics, segmentation, profiling), using these insights to evolve product offering and customer engagement. - Turn insights into business/brand plans - Support marketing strategy with business potential analysis to provide actionable business strategy recommendations * - Analyze end to end of the consumer journey, using SQL queries for example, to generate insights and strategic recommendations to optimize relationships with consumers. - Develop approaches to integrate quantitative and qualitative insights and structured and unstructured data into a holistic view of customers. - Use predictive analytics and machine learning to enable business decisions concerning prospective student consumer journey from awareness = > consideration = > conversion = > loyalist. - Build deep knowledge and understanding of customers, channels, market and competition in order to influence new product development, drive brand leadership * - Model, design and implement reporting dashboards that track key business metrics. - High level database design - Manage reporting deliverables - actual business performances, monthly forecasts, annual budgeting - Maintenance of reporting dashboards. * - Knowledge of financial data analysis (P&L etc.): - Perform financial & ROI analysis to support the commercial team. - Identify business cost saving, revenue uplift and any other operational or strategic benefits * - Perform special projects as required **Requirements**: - University degree in statistics, mathematics, information systems, computer science, engineering, economics or other disciplines for which quantitative methods are an important part. - Minimum 7 years of work experience that directly relates to this job specification. - Possess machine learning or programming skills and will be able to manipulate data. - Experience utilizing both qualitative analysis (e.g., content analysis, hypothesis testing) and quantitative analysis techniques (e.g., clustering, regression, pattern recognition, descriptive and inferential statistics). - Experience with dashboard development and data reporting for business and commercial stakeholders - Demonstrated success presenting complex data (qualitative and quantitative) in a clear and compelling manner that inspires action. Competencies - Demonstrated skills in selecting the right statistical tools given a data analysis problem. - Experience in business intelligence and efficiently build dashboards and reporting requests through data modelling, designing and implementing a data warehouse. - Ability to simplify complex analysis into clear explanation and visualization - Possess a wide breadth of abilities: curiosity, storytelling, product sense, and resourcefulness. Curiosity: - A desire to go beneath the surface and distill a problem into a very clear set of hypotheses that can be tested. - Ability to use this curiosity to look at the available data sets and sources to solve business questions. - Storytelling: - The ability to communicate your findings effectively to non-technical stakeholders. - Distill a quantitative result into something (be it words, pictures, charts, etc.) that everyone can understand) Product Sense: - The ability to use the story to create a new product or change an existing product in a way that improves company goals and metrics. Resourcefulness: - The creativity to do all the above things on a deadline or on constrained resources. - Commercial knowledge & understanding especially sales and marketing. - Experienced in translating analysis results into business recommendations. * Competencies (Behavioral) - A data dri