The Senior Data Scientist rapidly navigates from identifying priorities/helping to generate ideas to implementing the solution. He/she has a passion to see own work translated in business results.
He/she oversees/supports Advanced Analytics (AA) activities within his/her area for EPD globally and ensures that business objectives are tracked and achieved (in collaboration with key stakeholders).
With increasing experience, he/she is responsible for understanding core business challenges and needs and for deriving a suitable global AA roadmap based on this understanding in collaboration with key stakeholders.
He/she actively takes part in the development, deployment, and integration of prioritised Advanced Analytics solutions in collaboration with local/regional cross-functional teams and/or external partners, including e.g.,
Setting up / leading/supporting ideation and scoping sessions with business stakeholders
Choosing and using the right analytical libraries, programming languages, and frameworks for each task
producing high-quality code that allows us to put solutions into production
refactoring code into reusable libraries, APIs, and tools
Help build and maintain close contact with key business stakeholders and relevant communities
Build effective and efficient AA solutions to business needs, leveraging available market resources as much as possible
Help derive and continuously refine AA guidelines and standards through synthesizing learnings from prioritized AA initiatives (“learning while doing and driving impact”).
Requirements & Skills:
Master’s in a relevant field (e.g., applied mathematics, computer science, engineering, applied statistics)
At least 4 years (senior) of relevant working experience, ideally in a pharma environment
Good /solid experience working on full-life cycle data science; experience in applying data science methods to business problems (experience in the financial/commercial or manufacturing/supply chain areas a plus).
Strong experience in e.g., data mining, statistical modelling, predictive modeling, and development of machine learning algorithms
Practical experience in deploying machine learning solutions
Programming experience in R or Python and ideally also in object-oriented programming, such as e.g., C, C++, Java
Good understanding of good software engineering principles
Good knowledge of testing frameworks and libraries
Experience with AWS / Sagemaker is a plus
Proven problem-solving ability in international settings
Strong background in analytics and statistics
Proven communication skills
Intrinsic motivation to guide people and make Advanced Analytics more accessible to a broader range of stakeholders. Ability to work with cross-functional teams and bring business and data science closer together – consultancy experience a plus
Fluency in English is a must, additional languages are a plus
