Data Science Lead
MilliporeSigma

Job Info

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A career with MilliporeSigma 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. MilliporeSigma is a business of Merck KGaA, Darmstadt, Germany.

Your Role:

• Computer Scientist, Cheminformatics Technology Development will work closely with the Chemistry team, product development team, and commercial teams along with external collaborators to advance our core cheminformatics capabilities.
  
• Design and lead development of novel AI/ML driven platforms and algorithms for predicting retrosynthetic pathways.
  
• Contribute to the further development of the retrosynthetic software and associated technology according to roadmap of product development roadmap
  
• Identify further refinements, expanded capabilities using knowledge of other software and related technology
  
• Stay on top of latest developments in the field of machine learning, advanced analytics and cheminformatics and lead the internalization of promising approaches. Actively seeks opportunities to enhance software.
  

Who You Are:

Minimum qualifications:

• 3+ years of cheminformatics experience, preferably in retro- and forward-synthesis
  
• 3+ years of ML model development in chemistry domain, generative modeling, and deep learning
  
• Work permit for USA
  

Preferred qualifications:

• Experience in machine learning, deep learning, statistical methodology, predictive modeling, and algorithm development to analyze large sets of chemical data.
  
• Familiarity with cheminformatic tools and libraries such as RDKit .
  
• In-depth understanding of deep learning algorithms such as Graph Convolutional Networks, Transformer architecture, Generative Models.
  
• Experience with one or more of deep graph learning (e.g., graph convolutional networks, neural message passing networks), natural language processing (NLP), and generative models (e.g., VAE, GAN, Flow).
  
• Experience with Monte-Carlo tree search, genetic algorithms, and reinforcement learning.
  
• Documented experience in coding in Python, git or otherwise
  
• Team player, willing to work across disciplines and learn independently
  
• Self-motivated and energetic, excited to tackle the challenges associated with cutting edge science
  
• Fluent in English
  

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 responsibility early on and support you to draw your own career map that is responsive to your aspirations and priorities in life. Join us and bring your curiosity to life!

Curious? Apply and find more information at https://jobs.vibrantm.com

The Company is an Equal Employment Opportunity employer. No employee or applicant for employment will be discriminated against on the basis of race, color, religion, age, sex, sexual orientation, national origin, ancestry, disability, military or veteran status, genetic information, gender identity, transgender status, marital status, or any other classification protected by applicable federal, state, or local law. This policy of Equal Employment Opportunity applies to all policies and programs relating to recruitment and hiring, promotion, compensation, benefits, discipline, termination, and all other terms and conditions of employment. Any applicant or employee who believes they have been discriminated against by the Company or anyone acting on behalf of the Company must report any concerns to their Human Resources Business Partner, Legal, or Compliance immediately. The Company will not retaliate against any individual because they made a good faith report of discrimination.

Job Requisition ID: 229170

Location: Burlington

Career Level: D - Professional (4-9 years)

Working time model: full-time

This job has expired.