{"schemaVersion":"jobsearcher.job.v1","id":"0ed3e756cceeb434ff0ab500","url":"https://jobsearcher.com/jobs/0ed3e756cceeb434ff0ab500","canonicalUrl":"https://jobsearcher.com/jobs/0ed3e756cceeb434ff0ab500","title":"Data Partner/Practice Lead - Remote With Travel","description":"Data Science And AI/ML Solutions Leader Extensive experience (10-12+ years) in data science, machine learning, AI, or related domains, with a proven track record of leading successful projects and teams within a system integration context. Strong understanding of system integration principles, architectures, and technologies, with the ability to design and implement data science and AI/ML solutions that seamlessly integrate with existing systems and processes. Focused experience on Life Sciences Pharma R&D & Medical Devices industry is MUST, along with relevant certifications in data science, AI, or related fields. Deep working knowledge of Generative AI and the latest market trends and create a roadmap and vision for our clients. 4-5 years of experience working as a data science practice leader at Big 4 or boutique consulting firms Experience in solutions architecture. Technical domains such as AI/ML, multimodal ML, model evaluation, MLOps, MLSecOps, ML training, inference, data engineering, data science, fine-tuning Proficiency in programming languages such as Python, R, and Java, along with experience with data and AI libraries and frameworks (e.g., TensorFlow, PyTorch, scikit-learn). Experience in advanced analytics tools (Python, R) along with applied mathematics, ML, Deep Learning frameworks (such as TensorFlow), and ML techniques (such as random forest and neural networks). Experience in Machine Learning solutions (using various models, such as Linear/Logistic Regression, Support Vector Machines, Deep Neural Networks,..) Developing AI and ML models in real-world environments and integrating AI and ML using cloud-native or hybrid technologies into large-scale enterprise applications.","company":"Dignify Solutions","rawCompany":"dignify solutions","isRemote":true,"isActive":false,"createdAt":"2026-08-21T02:35:40.197Z","occupations":[{"code":"15-2051.00","title":"Data Scientists","slug":"data-scientists"},{"code":"15-1243.01","title":"Data Warehousing Specialists","slug":"data-warehousing-specialists"},{"code":"11-3021.00","title":"Computer and Information Systems Managers","slug":"computer-and-information-systems-managers"}],"industries":[{"code":"541690","title":"Other Scientific and Technical Consulting Services","slug":"other-scientific-and-technical-consulting-services"},{"code":"541512","title":"Computer Systems Design Services","slug":"computer-systems-design-services"},{"code":"541511","title":"Custom Computer Programming Services","slug":"custom-computer-programming-services"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Data Partner/Practice Lead - Remote With Travel","description":"Data Science And AI/ML Solutions Leader Extensive experience (10-12+ years) in data science, machine learning, AI, or related domains, with a proven track record of leading successful projects and teams within a system integration context. Strong understanding of system integration principles, architectures, and technologies, with the ability to design and implement data science and AI/ML solutions that seamlessly integrate with existing systems and processes. Focused experience on Life Sciences Pharma R&D & Medical Devices industry is MUST, along with relevant certifications in data science, AI, or related fields. Deep working knowledge of Generative AI and the latest market trends and create a roadmap and vision for our clients. 4-5 years of experience working as a data science practice leader at Big 4 or boutique consulting firms Experience in solutions architecture. Technical domains such as AI/ML, multimodal ML, model evaluation, MLOps, MLSecOps, ML training, inference, data engineering, data science, fine-tuning Proficiency in programming languages such as Python, R, and Java, along with experience with data and AI libraries and frameworks (e.g., TensorFlow, PyTorch, scikit-learn). 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