Level

Roche

Data Modeling Expert

Roche is hiring a Data Modeling Expert. Level rates it ; you can apply on Roche.

Level's read on this job

  • Level rates this role Works on AI ●●●○: the daily work is on AI products, without building the model.
  • Tools and skills the posting cites include data modeling, semantics and ontologies.
  • Level classifies it as a senior role.
  • Level lists 1,200+ other open roles at Roche.
  • The role was posted in the last few days.

AI in this role

Data modeling expert building FAIR data ecosystems and semantics to enable computational tools and AI algorithms across R&D organizations.

data-modelingsemanticsontologiesdata-standardsfair-data

At Roche you can show up as yourself, embraced for the unique qualities you bring. Our culture encourages personal expression, open dialogue, and genuine connections,  where you are valued, accepted and respected for who you are, allowing you to thrive both personally and professionally. This is how we aim to prevent, stop and cure diseases and ensure everyone has access to healthcare today and for generations to come. Join Roche, where every voice matters.

The Position

A healthier future. It’s what drives us to innovate. To continuously advance science and ensure everyone has access to the healthcare they need today and for generations to come. Creating a world where we all have more time with the people we love. That’s what makes us Roche. 

Advances in AI, data, and computational sciences are transforming drug discovery and development. Roche’s Research and Early Development organisations at Genentech (gRED) and Pharma (pRED) have demonstrated how these technologies accelerate R&D, leveraging data and novel computational models to drive impact. Seamless data sharing and access to models across gRED and pRED are essential to maximising these opportunities. The new computational sciences Center of Excellence (CoE) is a strategic, unified group whose goal is to harness this transformative power of data and Artificial Intelligence (AI) to assist our scientists in both pRED and gRED to deliver more innovative and transformative medicines for patients worldwide.

Within the CoE organisation, the Data and Digital Catalyst organisation drives the modernisation of our computational and data ecosystems and integration of digital technologies across Research and Early Development to enable our stakeholders, power data-driven science and accelerate decision-making.

Join the newly formed Computational Sciences Center of Excellence (CoE) as a Data Modeling Expert, a key role within our Data Connectivity team. You will serve as a key contributor in the data modeling, semantics, ontologies, and standards space, ensuring our data are FAIR (Findable, Accessible, Interoperable, and Reusable), high-quality, and trustable; enabling scientists, computational tools, and AI algorithms from across our Research and Early Development (REDs) organizations to effectively leverage and utilize these data assets. 

As our Data Modeling Expert, you will:

  • Act as a key subject matter expert on data modeling, ontologies, semantics, and standards efforts, interfacing closely with business/scientific stakeholders and informatics/engineering colleagues.

  • Translate complex scientific requirements from various parts of R&D into clear draft data models that can be leveraged by the wider FAIR data modeling team.

  • Independently contribute to and on occasion drive the development of data models and standards and/or information architecture solutions potentially leading function-level efforts related to FAIR data processes relating to data modeling, standards development and/or information architecture.

  • Independently contribute to and on occasion drive strategies that ensure pan-RED Roche data is ready for AI/ML (AI data readiness), potentially leading tactical efforts around AI/data policies in partnership with other colleagues in the broader team.

  • Independently contributes to and on occasion drive efforts that enable data quality tracking, potentially leading strategies that allow us to track and measure data quality (e.g. tracking how well annotated xRED data is).

  • Foster a OneRoche data-centric mindset within the team, advocating for data standards, governance, and FAIR principles.

  • Contribute to the development, implementation and improvement of Data Governance strategies as it relates to data standards.

Who You Are:

  • You hold a Master's degree or higher in a scientific or technical field.

  • Experienced in Data Governance, Data Standards, Data Modeling, Ontology Development, or related fields.

  • You are proficient in one or more critical relevant scientific or data domains, and are able to provide leadership to initiatives based on that knowledge.

  • You are an exceptional communicator with strong networking capabilities, able to build relationships and lead effectively in a matrixed organization.

  • You have experience working within a Research & Development organization and have a deep understanding of its processes and data handling activities.

This role is based onsite at our Welwyn office.

#ComputationCoE

 

 

Who we are

A healthier future drives us to innovate. Together, more than 100’000 employees across the globe are dedicated to advance science, ensuring everyone has access to healthcare today and for generations to come. Our efforts result in more than 26 million people treated with our medicines and over 30 billion tests conducted using our Diagnostics products. We empower each other to explore new possibilities, foster creativity, and keep our ambitions high, so we can deliver life-changing healthcare solutions that make a global impact.


Let’s build a healthier future, together.

The statements herein are intended to describe the general nature and level of work being performed by employees, and are not to be construed as an exhaustive list of responsibilities, duties, and skills required of personnel so classified. Furthermore, they do not establish a contract for employment and are subject to change at the discretion of Roche Products Ltd. At Roche Products we believe diversity drives innovation and we are committed to building a diverse and flexible working environment. All qualified applicants will receive consideration for employment without regard to race, religion or belief, sex, gender reassignment, sexual orientation, marriage and civil partnership, pregnancy and maternity, disability or age. We recognise the importance of flexible working and will review all applicants’ requests with care. At Roche difference is valued and we are proud to be an equal opportunity employer where you are encouraged to bring your whole self to work.

How we rate this

Data Modeling Expert at Roche rates 60 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.

Classification

Works on AI. The daily work is on AI products, without building the model.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

Data ModelingSemanticsOntologiesData StandardsFair Data

Questions you could be asked

  1. Tell me about a project where data modeling was part of your work. What did you do?
  2. Tell me about a project where semantics was part of your work. What did you do?
  3. Tell me about a project where ontologies was part of your work. What did you do?
  4. Tell me about a project where data standards was part of your work. What did you do?
  5. Tell me about a project where fair data was part of your work. What did you do?

Adapt your resume

  • List these exact terms on your resume: Data Modeling, Semantics, Ontologies, Data Standards, and Fair Data. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
  • Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.

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