The Data Scientist is the main driver behind advanced analytics supporting supply chain processes. The successful Data Scientist will translate business needs into analytic questions; conduct data exploration and model specification; design and perform rigorous analyses of operational, customer, and financial data; and translate these analytic findings into leading information for our business partners. The chosen candidate would act as an advisor for executive and management level decision makers. This individual would also provide direction to IT on data governance and industry best practices with a lens towards agility and efficiency.Key Responsibilities:
Consult with internal and external stakeholders to determine how best to apply descriptive analysis and/or statistical learning to support business objectives across AbbVies Supply Chain.
Demonstrate a thorough understanding of concepts related to statistical methods and operations research and how to use them for solving real world problems.
Apply linear models, machine learning algorithms, times series forecasting, and modern optimization methods (i.e. metaheuristics) to understand and/or predict events impacting supply chain
Understand the guidelines needed to build credible and efficient simulation models used to inform the decision-making process
Collaborate with subject matter experts and data engineers to deploy advanced analytic solutions into the operational environments.
Adhere to agile project management frameworks and set the direction of data science initiatives
Effectively communicate technical concepts to a non-analytic audience
Masters in Statistics, Analytics, Operation Research, Computer Science, Mathematics, Economics, or related field. Will also consider candidates with a bachelors degree in these fields, plus 5 years of relevant professional work experience with an outstanding track record
Proficiency in R is required. Knowledge of RShiny is a plus. A Python skillset is also valuable and can be accommodated
Practical experience with times series forecasting, monte carlo analysis, spatial analysis, and/or machine learning (random forest, neural nets, SVM, etc)
Familiarity with navigating in both a relational (Teradata-based) and non-relational (Hadoop) environment. SQL skillset is strongly desired. Knowledge of Java/Scala/Apache Spark is a bonus
Practiced in exploratory data analysis (EDA) and manipulating large data sets
Capable of accessing external data sources through various APIs (e.g. google distance matrix, quandl financial data, etc)
Good interpersonal skills and ability to present advanced analytical concepts to senior management
Strong analytical and problem-solving skills. Analytic experience in supply chain is sought after, but not a requirement
Self-starter and intellectually curious with a strong desire to improve business processes through innovation
Motivated to gain the full business understanding behind each analytical request
Functional leadership, Senior Management, Sales Entities, Brand Team, Planning, Distribution, Logistics, Project teams, ITAdditional Information