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Data Partner/Practice Lead - Remote
Remote / Online - Candidates ideally in
Minneapolis, Hennepin County, Minnesota, 55400, USA
Listed on 2026-02-07
Minneapolis, Hennepin County, Minnesota, 55400, USA
Listing for:
The Dignify Solutions, LLC
Remote/Work from Home
position Listed on 2026-02-07
Job specializations:
-
IT/Tech
AI Engineer, Machine Learning/ ML Engineer
Job Description & How to Apply Below
Qualifications
- 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., Tensor Flow, PyTorch, scikit-learn).
- Experience in advanced analytics tools (Python, R) along with applied mathematics, ML, Deep Learning frameworks (such as Tensor Flow), 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.
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