AI Research Scientist

We're seeking a highly skilled AI Research Scientist to spearhead the development of cutting-edge predictive models in chemistry.

The ideal candidate will play a pivotal role in building clients' AI products, driving innovation through the integration of AI/ML methodologies and fostering collaboration across interdisciplinary teams to achieve organizational goals in pharmaceutical development.

Key Responsibilities:

• Develop and enhance sophisticated AI-powered prediction models to predict and optimize chemical formulations, leveraging expertise in cheminformatics data analysis and large-scale data handling.

• Collaborate with software engineers to integrate advanced computational models into the AI platform, utilizing cloud platforms (AWS, Azure, or GCP) for large-scale computations.

• Analyze extensive datasets from chemistry data and R&D experiments to uncover patterns, trends, and optimization opportunities, applying statistical and machine learning techniques.

• Develop and validate robust statistical and machine learning models to improve prediction accuracy and reliability, ensuring seamless integration of scientific methods into practical applications.

• Improve the computational efficiency and scalability of existing models to handle diverse customer needs, minimizing redundancy and controlling operational expenses.

• Drive efficient use of computational and cloud resources, ensuring compliance with industry standards and best practices.

• Work closely with domain experts, software engineers, and project managers to ensure the successful integration of scientific methods into practical applications, delivering insights and solutions based on predicted outputs.

• Communicate findings and recommendations effectively to technical and non-technical stakeholders, collaborating with customers to understand their R&D challenges and tailoring the platform to address specific use cases.

• Ensure alignment with customer sustainability and performance goals, providing high-quality results that meet or exceed expectations.

Qualifications:

• Bachelor's or Master's in Computer Science, Data Science, Cheminformatics, or Computational Chemistry, or related fields.

• Course certificates in Data Science, Machine Learning, or related fields.

• 6+ years of total experience, 3+ relevant drug discovery experience with demonstrated impactful contributions to small-molecule programs.

• 4+ years of experience in data modeling, computational analysis, or similar roles, preferably in manufacturing, R&D, or chemical industries.

• Proficiency in programming languages (Python, R, or similar), AI/ML tools (TensorFlow, PyTorch, or sci-kit-learn), and data visualization tools.

• Background or project work in materials physics/chemistry or a related field is an added advantage, not mandatory.

Technical Skills:

• Programming experience in Python (preferred), R, or similar languages.

• Hands-on experience with AI/ML tools like TensorFlow, PyTorch, or sci-kit-learn.

• Expertise in cheminformatics data analysis and large-scale data handling.

• Familiarity with cloud platforms (AWS, Azure, or GCP) for large-scale computations.

• Experience with databases (SQL/NoSQL) and data visualization tools.

Soft Skills:

• Strong problem-solving and critical-thinking abilities.

• Excellent communication skills to convey complex ideas to varied audiences.

• Team player with a collaborative mindset.

• Efficient and flexible disposition, able to rapidly learn new fields and use data science and machine learning to improve decision-making and workflows.