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Tier-1 employer and Bangalore location increase competition, but PhD chemometrics specialization limits candidate pool.
Highly domain-specific chemometrics, spectroscopy, and process-data expertise reduces cross-industry transferability.
PhD, publications, and deep chemometrics and physics-informed ML expertise are mandatory filters.
Develop and implement advanced chemometric, statistical, and physics/chemistry-informed AI models to optimize and control complex chemical and industrial processes.
Translate diverse chemical and process data into actionable insights for process monitoring, quality control, predictive maintenance, and R&D innovation.
Collaborate with chemists, engineers, and domain experts to ensure model robustness, scalability, and scientific validity for real-time industrial application.
PhD in Applied Statistics, Data Science, Chemometrics, Mathematics, or Engineering with experience in large-scale process data modeling and optimization.
Proven expertise in chemometric and multivariate statistical methods applied to analytical chemistry data (chromatography, spectroscopy).
Strong AI skills including hands-on experience with reinforcement learning, GANs, meta-learning, active learning, or generative AI applied to industrial process modeling.
Work Experience Required: Significant experience delivering R&D and consultancy projects with strategic business impact.
Experienced technical expert operating at the intersection of mathematics, statistics, chemistry, and digital technologies focused on industrial chemical systems.
Experienced in deploying scalable machine learning and statistical solutions within multidisciplinary teams from research through to real-world implementation.
Experienced in publishing scientific research and developing intellectual property in chemometrics, AI, or process data optimization domains.