Resumo da vaga

Data Scientist- Algorithms, Community Support

Requisitos e responsabilidades

Conteúdo da vaga extraído em seções para revisão mais rápida.

Details

  • Implement advanced techniques to automate the LLM evaluation process with high efficiency and quality.
  • Scale the high-quality synthetic datasets curation across various CS domains for training and evaluating LLM.
  • Build LLM/ML models to understand customer issues based on diverse datasets and identify failure modes and opportunities for improvement.
  • Build personalization models to offer differentiated experiences and maximize business impact.
  • Discover Opportunities: Identify high-impact business opportunities through data exploration and model prototyping, and translate business problems into scientific formulations.
  • Uncover Insights: Analyze structured and unstructured data to uncover meaningful insights and craft actionable proposals that help shape strategy.
  • Build and Ship: Build and deploy production LLM/ML models that directly contribute to the launch of data-driven products, leveraging AI tools to enhance efficiency and impact.
  • Collaborate Cross-Functionally: Build strong relationships with cross-functional partners across Product, Design, Engineering, Operations, and Analytics to drive collaboration and innovation.
  • Influence Decisions: Communicate learnings to leaders and stakeholders in a clear, compelling manner that drives informed, data-driven decision-making.
  • Empowerment: Think strategically about how to scale and evolve data science capabilities within your domain, contributing to the long-term vision for how science drives platform outcomes.
  • 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, observation causal inference skill is a plus.
  • Proven ability to communicate clearly and effectively to audiences of varying technical levels.
  • Ability to translate complex findings and results into compelling narratives that drive impact.
  • Excellent project management, communication, and collaboration skills.
  • A product-oriented mindset, with the ability to apply conceptual and innovative thinking to develop and implement solutions that consider the user experience.
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