Machine Learning Expert, Pre Clinical Research - Bayer Corporation

At Bayer we’re visionaries, driven to solve the world’s toughest challenges and striving for a world where 'Health for all Hunger for none’ is no longer a dream, but a real possibility. We’re doing it with energy, curiosity and sheer dedication, always learning from unique perspectives of those around us, expanding our thinking, growing our capabilities and redefining ‘impossible’. There are so many reasons to join us. If you’re hungry to build a varied and meaningful career in a community of brilliant and diverse minds to make a real difference, there’s only one choice.

Machine Learning Expert, Pre Clinical Research  

This role will spearhead the strategic application of machine learning technology in the preclinical phases of drug development. Our objective is to harness advanced machine learning techniques to assess the safety and efficacy of lead compounds, streamline safety prediction, and optimize lead compound development. Your expertise will be instrumental in directing the application of these innovative approaches to enhance the efficiency and effectiveness of our preclinical research pipelines.

YOUR TASKS AND RESPONSBILITIES

The primary responsibilities of this role, Machine Learning Expert - Pre-Clinical Research, are to:

• Lead the design and strategic integration of machine learning to maximize safety and efficacy assessment of lead compounds in vitro and in vivo through advanced analytical techniques, focusing on toxicology, pharmacokinetics/pharmacodynamics, molecular biology, pathology, drug formulation, and biochemistry;
• Guide the selection and adaptation of machine learning techniques to address specific scientific questions in toxicology, pharmacokinetics/pharmacodynamics, molecular biology, pathology, drug formulation, and biochemistry, involving extensive data mining and pattern recognition in complex datasets;
• Evaluate and recommend computational frameworks and platforms for handling extensive biological data;
• Provide thought leadership and strategic insights to enhance machine learning capabilities in preclinical research, proposing innovative solutions for breakthroughs;
• Stay updated on industry trends and advancements in machine learning, bioinformatics, and preclinical drug development, particularly related to safety and efficacy assessment of lead compounds;
• Collaborate in the design and development of machine learning models, ensuring scalability, reproducibility, and maintainability, and applying MLOps practices to streamline candidate development and optimize lead compounds;
• Utilize experience with Agile and Scrum practices to facilitate cross-functional collaboration and ensure efficient and effective delivery of machine learning projects;
• Enforce rigorous software lifecycle management protocols for machine learning applications, maintaining high standards of code quality, data integrity, and ethical AI principles;
• Champion the VACC (Vision, Accountability, Courage, and Collaboration) leadership principles by modeling behaviors that promote bold decision-making, clear accountability, and transparent communication;
• Embrace and foster Dynamic Shared Ownership (DSO) by actively promoting an inclusive culture where ideas and decisions are shared across teams, empowering team members and encouraging ownership and participation in project outcomes;
• The primary location for this role is Cambridge, MA or Whippany, NJ.  Relocation may be offered for this role.
• Visa sponsorship may be offered for this role.

WHO YOU ARE

Bayer seeks an incumbent who possesses the following:

Required Qualifications:

• PhD in Computational Biology, Bioinformatics, Computer Science, or related field, with over 10 years of experience in machine learning applications, specifically in preclinical research;
• Proven track record of strategic leadership and effective team management in an innovation-driven field;
• Strong understanding and application of MLOps principles, with experience in HPC environments and cloud platforms;
• Proficiency in software lifecycle management and Agile methodologies, with a collaborative and dynamic work approach;
• Extensive experience in managing the lifecycle of machine learning applications in preclinical research;
• Innovative thinking and problem-solving in high-throughput data environments;
• Excellent collaboration, interpersonal, and communication skills, with the ability to engage with stakeholders at all organizational levels;
• Deep understanding of preclinical drug development processes, particularly safety and efficacy assessment of lead compounds;
• Established presence in the scientific community with contributions to major conferences and publications;

Preferred Qualifications:

• Experience with regulatory considerations for computational tools in pharmaceutical research;
• Demonstrated ability to adapt and thrive in a rapidly evolving technological landscape;
• 10+ years of industry experience, with 4+ years specifically in preclinical research machine learning applications.

This posting will be available for application until at least 08-23-2024 .

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