Responsibilities
• Build analytics products comprising of predictive and prescriptive models using machine learning techniques to address a multitude of questions, but largely relating to the commercial side of the business.
• Act as the key point of contact between the Analytics CoE and the broader Sales, Revenue Management and Commercial teams in driving new thinking and concepts in this area.
• Benchmarking, baselining, quantifying & tracking business value extracted through the Analytics solutions.
• Educating key contacts in the business on what analytics, how to get value from it and making analytical initiatives a part of each function’s business plans, in essence, driving an Analytics Culture throughout the organization.
3. Qualifications and Technical Competencies Required
• Bachelor’s degree in quantitative field like computer science, engineering, statistics, mathematics or related field required; advanced degree is a plus
• 2 years’ experience as a data scientist, building predictive and/or prescriptive models
• Knowledge of statistical and machine learning techniques (regression, decision trees, clustering, neural networks, etc.)
• Experience in working with large datasets and relational databases in SQL
• Programming experience in R and/or Python; familiarity with Databricks and Azure ML is an asset
• Analytical mind and business acumen
• Problem-solving aptitude
• Good communication and presentation skills
