Summary:
The Enterprise Data and Analytics group at Cencora is looking for a Data Scientist-II interested in working with data to answer questions about sourcing, pricing, and distributing pharmaceuticals across the United States. Individuals within the Data Scientist role work closely with business stakeholders, Analysts, Data Engineers, Data Visualization Specialists and other team members to turn data into critical information and knowledge that can be used to make sound organizational decisions. They need to be creative thinkers and propose innovative ways to look at problems by using data mining (the process of discovering new patterns from large datasets) approaches across a wide range and variety of data assets. They will need to validate their findings using an experimental and iterative approach. Also, Data Scientists will need to be able to present back their findings to the business by exposing their assumptions and validation work in a way that can be easily understood by their business counterparts.
Core responsibilities focus on:
Work Complexity:
- Designs experiments, tests hypotheses and builds analytic models.
- Conducts data analysis and designs and develops moderately complex analytic algorithms.
Business Requirements:
- Works with business stakeholders and others to identify the business requirements and the expected outcome.
- Helps model and frame business scenarios that are meaningful and which impact on critical business processes and/or decisions.
- Gains knowledge of internal and external data sources and business data domain expertise.
Data Requirements:
- Collaborates with subject matter experts to select relevant sources of information.
- Translates business requirements into semantic access, conceptual, logical and/or physical data models.
Analytics:
- Works with others to solve client analytics problems and documents results and methodologies.
- Performs experimental design approaches to validate findings or test hypotheses.
- Validates analysis by comparing appropriate samples.
- Employs the appropriate algorithm to discover patterns.
What your background should look like
Educational, Skillset Qualifications:
- Bachelor's degree in mathematics, statistics or computer science or related field.
- Typically requires at least three (3) or more years experience manipulating large datasets and using databases, and one (3) years' experience with a general-purpose programming language (such as Hadoop MapReduce, Spark or other big data frameworks, Java, Python).
- Experience using SQL to access and analyze data.
- Experience in the use of statistical packages.
- Experience with Azure and Databricks - desired but not required
- Familiarity with basic principles of distributed computing and/or distributed databases.
- Demonstrable ability to quickly understand new concepts-all the way down to the theorems- and to come out with original solutions to mathematical issues.
- Good communication and interpersonal skills.
- Knowledge of one or more business/functional areas.
- Ability to work well both independently as well as within a team oriented environment
- Ability to work hybrid on-site in Conshohocken, PA
Schedule
Full time
What the Team is Saying
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What We Do
Cencora is a leading pharmaceutical solutions organization centered on improving the lives of people and animals everywhere. With 46,000+ global team members, we have the opportunity to make a positive impact on healthcare in communities everywhere.
Our team members are empowered to activate their careers through a collective of tools and resources designed to support individual career interests and aspirations. We value our listening culture that actions real outcomes and our team members appreciate and recognize one another for contributions that are making a meaningful global impact.
No matter what your role is here, the work we do together has meaning. When you join our team, you become a crucial part of a greater purpose. We’re committed to supporting you personally and professionally, so we can achieve more together at the center of health.
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