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Principal Data Scientist, Consumer Experience

Posted 2024-11-14

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💎 Seniority level: Principal

🔍 Industry: E-commerce

Requirements:
NOT STATED
Responsibilities:
  • Work on a variety of impactful projects focused on Search and Recommendations.
  • Take ownership of projects from prototype to production.
  • Refine existing systems in retrieval, ranking, and query understanding.
  • Build aspects of search from the bottom up to improve user discovery experience.
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Related Jobs

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🔥 Principal Data Scientist, Consumer Experience
Posted 2024-11-20

🧭 Full-Time

💸 160000.0 - 260000.0 USD per year

🔍 ECommerce

  • MS or PhD in statistics, mathematics, analytics, computer science or another quantitative field AND 3+ years of experience as a data scientist in eCommerce or Logistics.
  • Or, 8+ years of experience as a data scientist in eCommerce or Logistics.
  • Hands-on experience in building ranking and recommendation models in production environments.
  • Experience applying descriptive statistics, machine learning, predictive modeling, and visualization techniques.
  • Expert knowledge in statistical and machine learning techniques, data science libraries, model deployment, and machine learning workflows.
  • Proficient in Python and related ML libraries (e.g., PyTorch), SQL, cloud platforms (e.g., AWS, GCP, Azure), and model development and deployment technologies (e.g., Databricks).
  • Excellent communication and presentation skills.

  • Build and enhance machine learning, statistical and causal models for product search, ranking and recommendation that support various business goals.
  • Work closely with product and engineering managers to develop and deploy solutions with cross-functional support.
  • Educate business and engineering partners on data science concepts.
  • Build models that support real-time events.
  • Present work to leadership and identify gaps in existing data.
  • Create data product specs and implement enhanced data tracking.
  • Share insights and best practices with Analytics team members.
  • Commit to automation and productionalized solutions.
  • Provide mentorship to less experienced data scientists.
Posted 2024-11-20
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