Hybrid
Full Time
In this job, I am accountable for:
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)Experience relevant for this job:
- Applied Math: Applied Statistics, Design of Experiments, Linear -1-2 year experience in data science application in Retail or CPG & Logistic Regression, Decision Trees, Forecasting, Optimization Preferred algorithms - Functional experience: Marketing, Supply Chain, Customer, - Tech: SQL, Hadoop, Python, Tableau, MS Excel, MS Merchandising, Operations, Finance or DigitalPowerpoint - Soft Skills: Analytical Thinking & Problem solving, Storyboarding
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