Senior AI Data Scientist: Lead Production ML & NLP

Requirements

• Proficiency in Python with a focus on AI libraries (e.g., TensorFlow, PyTorch, Keras)
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• Strong understanding of machine learning algorithms and deep learning architectures (e.g., CNNs, RNNs, GANs, Transformers)
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• Experience with natural language processing (NLP) techniques and frameworks (e.g., NLTK, SpaCy)
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• Familiarity with data manipulation and analysis libraries (e.g., Pandas, NumPy)
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• Knowledge of cloud platforms for AI deployment (e.g., AWS, GCP or Azure)
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• Experience with version control systems (e.g., Git) for collaborative development
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• 5+ years of experience in AI, machine learning, or related fields
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• Proven experience in developing and deploying AI models in production environments
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• Strong foundation in statistics and data analysis as it relates to AI
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• Familiarity with Agile methodologies and product development cycles
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• (Desirable) Experience with reinforcement learning and advanced AI techniques
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• (Desirable) Familiarity with ethical AI practices and regulations
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• (Desirable) Understanding of business applications and implications of AI technologies
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• (Desirable) Experience related to LLMs, Bedrock etc

What the job involves

• We are looking for an AI Data Scientist to join our Engineering team
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• As a Senior AI Data Scientist, you will lead the development and implementation of advanced artificial intelligence solutions
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• You will utilize machine learning techniques and deep learning architectures to solve complex problems and create innovative models that drive business value
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• You will work collaboratively with cross-functional teams to translate business requirements into AI-driven applications and insights
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• Design, develop, and deploy AI models and algorithms to address specific business challenges
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• Conduct research and experimentation to advance the state-of-the-art in AI and machine learning
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• Collaborate with product managers, engineers, and domain experts to identify opportunities for AI integration
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• Perform data preprocessing, feature engineering, and model selection for optimal performance
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• Evaluate and optimize AI models using performance metrics and model validation techniques
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• Communicate findings and insights effectively to stakeholders through data storytelling and visualization
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• Mentor and guide junior team members in AI concepts, tools, and best practices
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• Stay current with advancements in AI technologies and methodologies

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