Data, AI & Engineering Opportunities | Life Sciences

ADC Consulting; København; On-site; DKK 550,000 - 900,000; Full time

Job summary

ADC Consulting's Life Sciences Engineering & Analytics team in Copenhagen develops data pipelines and GenAI-based solutions for pharmaceutical and biotech clients. You will join a multidisciplinary group handling omics data, clinical data engineering, and AI-powered analytics across the R&D value chain.

The role emphasizes building scalable pipelines on cloud platforms like Databricks and leveraging Python, SQL, Spark, and MLflow, with opportunities to grow in GenAI initiatives within regulated

Qualifications

• Experience building data pipelines for life sciences data.
• Proficiency in Python, SQL and data analytics.
• Familiarity with GenAI or AI/ML tooling in regulated environments.

Responsibilities

• Design and implement scalable data pipelines for LS projects.
• Collaborate with data scientists and engineers to deploy AI solutions.
• Support cloud-based data platforms (Databricks) and CI/CD workflows.
• Assist in data governance and documentation across projects.

Skills

Data engineering

Python

SQL

GenAI

Tools

Databricks

Azure OpenAI

Spark

MLflow

Job description

Job Description

Are you interested in applying your data, engineering, cloud, or AI expertise within the Life Sciences industry? We are always looking for talented professionals to join the project teams driving this work forward.

At ADC, our Engineering & Analytics (Life Sciences) team is engaged across the full R&D data value chain for pharmaceutical and biotech organisations, from early discovery through clinical development. Our work spans scientific data engineering and GenAI solutions across omics, molecular data and AI engineering. We're also delivering data products and GenAI capabilities that support clinical development and operations within regulated LS environments.

How This Connects To Our Current Work

Our team is actively working across the following areas within Life Sciences:

• Omics engineering: building scientific data engineering and GenAI solutions across omics, molecular data and AI engineering, including data-analysis platforms.
• Bioinformatics: delivering end-to-end AI solutions built on industry best practices, combining deep domain knowledge with engineering excellence for clinical and biological data.
• Clinical data engineering: working with synthetic data flows, clinical data platforms and pipelines, and driving coding best practices in clinical development.
• LLM and generative AI applications in pharma: having hands-on experience building agentic and LLM-based products in regulated environments such as Databricks and Azure OpenAI.
• Data engineering: building and maintaining pipelines and migration engineering that regulated enterprise rollouts depend on.

We welcome applications from all seniority levels, from junior professionals to experienced specialists and senior consultants.

What You'd Be Working On

Our teams are currently working on a wide range of projects, including:

• Clinical, biomedical, omics, or pharmaceutical data
• Reliable and scalable data pipelines
• Cloud and data platforms such as Databricks
• Technologies such as Python, SQL, Spark, and MLflow
• Machine learning, LLMs, or generative AI within Life Sciences
• Bioinformatics or computational biology solutions

• Amsterdam Data Collective is an equal opportunity employer. To shape a better future, we value diversity and promote equality. No characteristics are discriminated against, as indicated in Directive 2000/78/EC. We encourage and welcome all applications. Additional arrangements or adjustments to support your application can be discussed further.