AI Specialist - Qualified Pipeline

November 12

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Data Meaning

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MicroStrategy Consultants • Data Warehousing • Business Intelligence Solutions • Project Management • Dashboard Customization & Design

51 - 200 employees

🤝 B2B

🏢 Enterprise

☁️ SaaS

Description

• Data Meaning is a front-runner in Business Intelligence and Data Analytics consulting. • Proactively building a pipeline of innovative and driven AI Specialist/Engineers. • Design, develop, and implement AI models and algorithms to solve business challenges. • Apply machine learning techniques to develop intelligent systems. • Collaborate with data scientists, software engineers, and business stakeholders to define AI-based solutions. • Analyze large datasets to extract meaningful insights and develop AI models for predictive analytics. • Deploy AI models into production environments and ensure their scalability and performance. • Continuously monitor AI systems and improve them based on performance metrics. • Research the latest AI trends and emerging technologies to drive innovation. • Provide technical support and guidance to junior team members on AI methodologies.

Requirements

• Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or related field. • 3+ years of experience working with AI/ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn). • Proficient in programming languages such as Python, R, Java, or C++. • Strong understanding of machine learning algorithms, neural networks, deep learning, and natural language processing (NLP). • Experience in working with large-scale datasets, data pre-processing, and data visualization tools. • Familiarity with cloud platforms (e.g., AWS, Google Cloud, Azure) for deploying AI solutions. • Ability to work in an agile environment and adapt to changing requirements. • Excellent problem-solving skills and the ability to think analytically and critically. • Strong communication skills, with the ability to explain AI concepts to non-technical stakeholders. • Experience in AI ethics and bias mitigation. • Knowledge of reinforcement learning and computer vision. • Experience with AI/ML model monitoring tools like MLflow or Kubeflow. • Contributions to AI research or publications in AI-related conferences.