Data Scientist

Responsibilities

• Identify high-impact business opportunities through data exploration and model prototyping; translate business problems into scientific formulations.
• Analyze structured and unstructured data to uncover insights and craft actionable proposals.
• Build and deploy production LLM/ML models that contribute to data-driven products.
• Implement advanced techniques to automate the LLM evaluation process with high efficiency and quality.
• Scale high-quality synthetic datasets curation across various CS domains for training and evaluating LLMs.
• Build LLM/ML models to understand customer issues based on diverse datasets, identify failure modes, and find opportunities for improvement.
• Build personalization models to offer differentiated experiences and maximize business impact.
• Collaborate cross-functionally with Product, Design, Engineering, Operations, and Analytics teams.
• Communicate learnings to leaders and stakeholders to drive data-driven decisions.
• Scale and evolve data science capabilities within the domain.

Requirements

• 2+ years of relevant industry experience (e.g. data/ML scientist, tech lead, junior faculty) and a Master’s degree or PhD in relevant fields.
• State-of-the-art knowledge of AI/ML models.
• Strong fluency in Python/R and SQL.
• Proven ability to communicate clearly and effectively to audiences of varying technical levels.
• Ability to translate complex findings into compelling narratives that drive impact.
• Excellent project management, communication, and collaboration skills.
• Product-oriented mindset with conceptual and innovative thinking applied to user experience.

Nice-to-Haves

• Observation causal inference skills.