Decision Scientist

- Identifying operational improvements and finding solutions by applying CI tools and techniques
- Responsible for completing tasks and transactions within agreed KPI's
- Knows and applies fundamental work theories/concepts/processes in own areas of work
Engaging with business & functional partners to understand business priorities; ask relevant questions and scope same into a analytical solution document calling out how application of data science will improve decision making
- In depth understanding of techniques to prepare the analytical data set leveraging multiple complex data set sources
- Building Statistical models and ML algorithms with practitioner level competency
- Writing structured; modularized & codified algorithms using Continuous Improvement principles (development of knowledge assets and reusable modules on GitHub; Wiki; etc) with expert competency
- Building easy visualization layer on top of the algorithms in order to empower end-users to take decisions - this could be on a visualization platform (Tableau / Python) or through a recommendation set through PPTs
- Working with the line manager to ensure application / consumption and also think beyond the immediate ask and spot opportunities to address the bigger business questions (if any)

Requirements

- Applied Math: Applied Statistics; Design of Experiments; Linear & Logistic Regression; Decision Trees; Forecasting; Optimization algorithms
- Tech: SQL; Hadoop; Python; Tableau; MS Excel; MS Powerpoint
- Soft Skills: Analytical Thinking & Problem solving; Storyboarding