Senior Data Scientist

We're looking for a Senior Data Scientist who can build and optimize our AI models that power our voice AI platform. You'll be the brain behind our technology, ensuring our AI can handle complex conversations while maintaining high accuracy and natural-sounding interactions.

Responsibilities:

• Own end-to-end model development: From requirement gathering and algorithm design to implementation and deployment, you'll shepherd ML features through their complete lifecycle.
• Build for conversational intelligence: Develop models that can handle hundreds of thousands of conversations per day with high accuracy and natural language understanding.
• Innovate through research: Stay current with cutting-edge NLP and speech technologies, read research papers, and implement state-of-the-art solutions that give us a competitive edge.
• Design ML pipelines: Create a robust, scalable machine learning infrastructure that can continuously improve from our growing conversation data.
• Optimize for performance: Identify and resolve model bottlenecks to ensure our voice AI delivers natural, real-time conversations without comprehension issues.

Requirements:

• 5+ years of experience in data science, machine learning, or a related field.
• Strong background in natural language processing (NLP) and conversational AI systems.
• Experience with speech recognition and text-to-speech technologies.
• Proficiency in Python and data science libraries (NumPy, Pandas, scikit-learn).
• Familiarity with deep learning frameworks (PyTorch, TensorFlow, Hugging Face).

AI and ML Skills:

• Experience fine-tuning language models (LLMs) for specific domains or tasks.
• Expertise in analyzing conversational data at scale and extracting actionable insights.
• Knowledge of customer intelligence systems and experience building data-driven applications.
• Understanding of speech-to-text optimization and improving transcription accuracy.

Data Engineering and Analytics:

• Experience with large-scale data processing (handling hundreds of thousands of conversations).
• Ability to design and implement data pipelines for continuous model improvement.
• Knowledge of feature engineering techniques for conversational data.
• Experience with A/B testing methodologies to evaluate model improvements.
• Familiarity with data visualization tools for presenting insights to stakeholders.

Startup Mindset:

• You've built and deployed ML models in production environments.
• Comfortable with a fast-paced environment where you'll own critical data science decisions.
• Collaborative approach - you work well with engineering teams, product, and founders.
• Growth-minded and excited about building customer intelligence systems that scale.