Job Location: North Chicago, IL
Purpose:
Describe the primary goals, objectives or functions or outputs of this position.
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.
Responsibilities:
List up to 10 main responsibilities for the job. Include information about the accountability and scope.
- Consult with internal and external stakeholders to determine how best to apply descriptive analysis and/or statistical learning to support business objectives across AbbVie’s 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, spatial analytics, 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
Qualifications:
- Masters in statistics, analytics, industrial engineering, computer science, mathematics, economics, or related field. Will also consider candidates with a bachelor’s degree in these fields, plus 5 years of relevant professional work experience
- Proficiency in R is required. A Python skillset is also valuable. Knowledge of Dataiku and RShiny is a plus.
- 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 and non-relational (e.g. MongDB) databases. 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
Key Stakeholders:
Functional leadership, Senior Management, Sales Entities, Brand Team, Planning, Distribution, Logistics, Project teams, IT
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