Senior Data Scientist – Genomics

Posted 2 Days Ago
Be an Early Applicant
Cluj-Napoca, Cluj, ROU
In-Office
Senior level
Biotech
The Role
Develop and productionize machine-learning, NLP, and LLM solutions for genomic and clinical data. Build variant classification, phenotype-genotype matching, cohort analysis, RAG applications, agentic workflows, and biomedical text-mining pipelines. Manage the full model lifecycle from experimentation through deployment, monitoring, and improvement while optimizing data-intensive algorithms through parallel and distributed computing. Collaborate with engineers, product managers, and clinical genetics experts to deliver accurate, reproducible, and reliable solutions.
Summary Generated by Built In

Overview  

 
At QIAGEN, we are driven by a simple but powerful vision: making improvements in life possible.  

We’re dedicated to revolutionizing science and healthcare for the better. From our entrepreneurial roots to our current global presence, we've grown into a force for positive change. With thousands of employees across six continents, collaboration is our greatest strength. We’re always striving to identify talented individuals to join our exceptional teams. 
 
We have played a pivotal role in shaping modern science and healthcare, and we're just getting started. If you're someone who thrives on new challenges, values diversity and wants to make a tangible difference in people's lives, then QIAGEN is the place for you. 

 

At QIAGEN, every day is an opportunity to make a real-life impact. 

 

Join us, grow with us, and together, let's shape the future of biological discovery. 

‎

About the opportunity

Join Franklin by QIAGEN and help turn complex genomic and clinical data into insights that support clinical genetics and research. Franklin combines curated scientific knowledge, bioinformatics pipelines and AI-driven analysis to help users interpret and report genomic data at scale.

In this Senior Data Scientist role, you will take algorithms and machine-learning solutions from experimentation through production, working across genomic data, NLP and LLM-based applications. Partnering with software engineers, product managers and clinical genetics experts, you will tackle complex scientific problems where accuracy, reproducibility and reliability matter.

Your tasks include

  • Designing, developing and productionizing machine-learning algorithms for genomic and clinical datasets, including variant classification and prioritization, phenotype-genotype matching and cohort-level analysis.
  • Building and evaluating LLM-powered applications, RAG solutions and agentic workflows, from early prototypes through production deployment.
  • Developing NLP and text-mining pipelines that transform scientific literature and other unstructured biomedical content into structured, actionable data.
  • Translating biological, clinical and product challenges into robust and scalable technical solutions in partnership with software engineers, product managers and domain experts.
  • Optimizing data-intensive algorithms using parallel and distributed computing approaches.
  • Managing the end-to-end model lifecycle, including experimentation, validation, testing, deployment, monitoring and continuous improvement.
  • Applying high standards of accuracy, reproducibility and production reliability while communicating technical findings and trade-offs clearly to different stakeholders.


Your profile

  • 5+ years of professional experience in data science, machine learning or applied research, including hands-on experience deploying ML solutions into production.
  • Strong Python expertise and practical experience with relevant data science and ML technologies such as NumPy, pandas, scikit-learn, PyTorch or TensorFlow.
  • Strong foundations in statistics, machine learning and algorithm design, with the ability to translate mathematical and statistical approaches into maintainable production solutions.
  • Hands-on experience with LLM applications, RAG or agentic workflows, combined with NLP or text-mining experience involving unstructured data.
  • Experience with parallel or distributed computing and solid software-engineering practices, including Git, testing, code review and maintainable code.
  • An MSc or PhD in Computer Science, Bioinformatics, Computational Biology, Data Science or another relevant quantitative discipline, or equivalent practical experience.
  • Fluent English communication skills and the ability to collaborate effectively across technical and scientific disciplines. Experience in genomics, clinical genetics, bioinformatics or healthcare data, including genomic formats such as VCF or BAM/CRAM, would be an advantage.

What we offer  

 

  • Bonus/Commission  

  • Local benefits   

  • Referral Program  

  • Volunteer Day  

  • Internal Academy (QIALearn)   

  • Employee Assistance Program   

  • Hybrid work (conditional to your role) 

 

Our people are the heartbeat of everything we do. Passion drives us as we push boundaries to innovate and evolve. We inspire with our leadership and make an impact with our actions. We cultivate a collaborative, supportive environment where each individual and team can flourish. We champion accountability and encourage entrepreneurial thinking.   

 

QIAGEN is committed to creating a diverse environment and is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, sex, age, national origin, religion, sexual orientation, gender identity, status as a veteran, or disability.  

Skills Required

  • 5+ years of professional experience in data science, machine learning, or applied research
  • Hands-on experience deploying machine-learning solutions into production
  • Strong Python expertise
  • Experience with NumPy, pandas, scikit-learn, PyTorch, or TensorFlow
  • Strong foundations in statistics, machine learning, and algorithm design
  • Hands-on experience with LLM applications, RAG, or agentic workflows
  • NLP or text-mining experience involving unstructured data
  • Experience with parallel or distributed computing
  • Software-engineering practices including Git, testing, code review, and maintainable code
  • MSc or PhD in Computer Science, Bioinformatics, Computational Biology, Data Science, or another relevant quantitative discipline, or equivalent practical experience
  • Fluent English communication skills
  • Ability to collaborate across technical and scientific disciplines
  • Experience in genomics, clinical genetics, bioinformatics, or healthcare data
  • Experience with genomic formats such as VCF or BAM/CRAM

QIAGEN Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about QIAGEN and has not been reviewed or approved by QIAGEN.

  • Flexible Benefits — Flexible work options (hybrid or remote where roles allow), flexible hours, sabbaticals, and site-specific childcare support work–life fit. Programs are presented as available where roles allow, signaling adaptable benefit design.
  • Wellbeing & Lifestyle Benefits — A global Employee Assistance Program for employees and immediate family, alongside broader wellbeing initiatives and community volunteering time, provides everyday support. Recognition for inclusive culture reinforces the emphasis on a supportive environment.
  • Parental & Family Support — Paid parental leave positioned as above typical U.S. norms and family-oriented offerings (e.g., on-site childcare at some locations) enhance caregiver support. Reports of solid PTO and holidays further strengthen family time.

QIAGEN Insights

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The Company
HQ: Hilden
6,000 Employees
Year Founded: 1984

What We Do

QIAGEN is the leading global provider of Sample to Insight solutions that enable customers to gain valuable molecular insights from samples containing the building blocks of life. Our sample technologies isolate and process DNA, RNA and proteins from blood, tissue and other materials. Assay technologies make these biomolecules visible and ready for analysis. Bioinformatics software and knowledge bases interpret data to report relevant, actionable insights. Automation solutions tie these together in seamless and cost-effective workflows. QIAGEN provides solutions to more than 500,000 customers around the world in Molecular Diagnostics (human healthcare) and Life Sciences (academia, pharma R&D and industrial applications, primarily forensics).

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