Associate Director, Qp Advanced Data Analytics

vor 2 Wochen

Lausanne, Schweiz Merck KGaA Darmstadt Germany Vollzeit

A career at our company is an ongoing journey of discovery: our 58,000 people are shaping how the world lives, works and plays through next generation advancements in Healthcare, Life Science and Electronics. For more than 350 years and across the world we have passionately pursued our curiosity to find novel and vibrant ways of enhancing the lives of others.

United As One for Patients, our purpose in Healthcare is to help create, improve and prolong lives. We develop medicines, intelligent devices and innovative technologies in therapeutic areas such as Oncology, Neurology and Fertility. Our teams work together across 6 continents with passion and relentless curiosity in order to help patients at every stage of life. Joining our Healthcare team is becoming part of a diverse, inclusive and flexible working culture, presenting great opportunities for personal development and career advancement across the globe.

**Your Role**
The Associate Director in Advanced Data Analytics (ADA) within our Quantitative Pharmacology (QP) organization is a strategic, scientific and cross-functional role of deploying and fostering next-generation model-informed drug development (MIDD) using ADA in order to increasingly take advantage of Real-World Data and support personalized medicine. This position will participate to QP activities to strengthen MIDD capabilities by developing and implementing ADA strategies/plans fully integrated into the overall preclinical and clinical plans across our projects and disease areas.

This position will be responsible for project-related Machine Learning (ML) / Deep Learning (DL) activities in QP either performed independently, under supervision and/or in collaboration with external CROs or academic institutions. Projects may include, but are not limited to, the analysis and integration of translational, biomarker and clinical data into ML/DL-enabled disease progression models, use of ML/DL to improve patient selection, exposure predictions, and trial designs. In using ML/DL-enabled drug-disease modeling to support project deliverables, you strongly contribute to decision making and critical achievements based on quantitative principles and partnering closely with global biostatistics, bioinformatics, clinical pharmacology expert leads, Medical Sciences, Research, and other quantitative disciplines.

Up to date scientific development in ML/DL and sharing expertise with colleagues is key as is participating in QP ADA research by developing your own innovative approach or mentoring fellows or overlooking academic externalized works. You contribute to external presentations and publications in the broader scientific/professional community of clinical pharmacology and pharmacometrics and represent QP in transactions with internal and external stakeholders.

**Who you are**:

- Ideally 5+ years (Bio)pharmaceutical industry and/or postdoctoral experiences with a doctorate (PhD, PharmD or MD) relevant in the related fields of Computer science, Mathematics, Engineering
- Strong theoretical knowledge and multi-year hands-on experience state-of-the-art ML (supervised, unsupervised, reinforcement learning) and DL methods (RNN, CNN, ensemble methods, transformers)
- Profound proficiency in programming languages like Python or R and full familiarity with ML/DL frameworks (Tensorflow, PyTorch, scikit-learn, Keras) and visualization libraries (Matplotlib, Seaborn, Bokeh).
- Strong hands-on experience in data cleaning, preprocessing and exploration tasks prior to data design
- Strong background in mathematics and statistics
- Industry experience, particularly in Healthcare, Biotech or Biopharma R&D would be an asset
- Knowledge of or ability to quickly learn endpoints, progression and treatments of diseases
- Familiarity with Linux and shell scripting
- Experience in PK/PD mathematical modeling, particularly in Pharmacometrics, would be an asset
- General knowledge of bioinformatics and approaches to generation, curation and analysis of -omics data (e.g., pharmacogenomics, transcriptomics, radiomics) is a plus
- Promoting ambassador for ADA use in clinical and quantitative pharmacology and/ or translational research internally and externally
- Proven ability of productive collaboration in a multi-discipline team, using effective communication and taking personal accountability for timely delivery of results
- Clear evidence of ability to make good judgement in complex situations and adapt to changing business needs by prioritizing multiple tasks
- Strong interpersonal skills and proactivity to cultivate a network of productive relationships in an international matrix environment
- Outstanding presentation, communication and organization skills; ability to lead, influence and motivate others

**What we offer**:With us, there are always opportunities to break new ground. We empower you to fulfil your ambitions, and our diverse businesses offer various career moves to seek new horizons. We trust you with resp

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