Job Summary:

The AI Research Scientist is responsible for developing and applying artificial intelligence and machine learning algorithms to drive business growth and improve decision-making processes.

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Key Responsibilities:

Research and Development

• Design, develop, and train AI and machine learning models to solve complex business problems and improve product offerings
• Conduct research in AI and machine learning to identify opportunities for innovation and improvement
• Collaborate with cross-functional teams to integrate AI and machine learning solutions into existing products and services

Data Analysis and Modeling

• Collect, preprocess, and analyze large datasets to identify patterns and trends
• Develop and apply statistical models and machine learning algorithms to solve business problems
• Create data visualizations and reports to communicate insights and results to stakeholders

Collaboration and Communication

• Work closely with stakeholders to understand business needs and develop solutions that meet those needs
• Communicate complex technical information to non-technical stakeholders through clear and concise reports and presentations
• Collaborate with other researchers and engineers to share knowledge and best practices

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Project Management

• Manage multiple projects simultaneously, prioritizing tasks and resources to meet deadlines and deliver results
• Develop and manage project plans, timelines, and budgets to ensure successful project execution
• Identify and mitigate risks to ensure project success

Requirements:

Education

• Ph.D. in Computer Science, Machine Learning, or a related field

Experience

• At least 3 years of experience in AI research and development, with a focus on machine learning and deep learning
• Experience with programming languages such as Python, R, or MATLAB
• Experience with AI and machine learning frameworks such as TensorFlow, PyTorch, or scikit-learn

Skills

• Strong understanding of machine learning and deep learning concepts, including supervised and unsupervised learning, neural networks, and reinforcement learning
• Experience with data preprocessing, feature engineering, and model evaluation
• Strong programming skills and experience with data visualization tools such as Matplotlib, Seaborn, or Plotly