Estimate domain traffic and engagement metrics (e.g., pages per visit, session duration) from clickstream data
Predict the most likely referral domain for a given event
Identify session acquisition channels (direct, organic, paid, etc.)
Development of quantitative frameworks for supplier criticality scoring and supplier portfolio optimization
Investigation related to supplier outages, data inconsistencies, and recovery/backfill artifacts
Design of proactive supplier risk mitigation approaches to minimize the impact of external data disruptions on customer-facing metrics
Identify socio-demographic characteristics of domain audiences to build detailed user profiles
Domain categorization by topic, industry, business type, and other attributes
URL analysis, including clustering and classification tasks

Strong practical experience in Data Science, Machine Learning, or Applied Statistics
Solid understanding of experimentation, hypothesis validation, and metrics-driven decision making
Excellent Python skills and experience building production-oriented solutions
Understanding of software engineering best practices: testing, reproducibility, and code quality
Strong SQL knowledge and experience working with analytical databases
Experience working with large-scale datasets and data pipelines
Takes ownership in ambiguous environments and proactively drives initiatives forward
Creates transparency around progress, risks, and decisions
Builds trust through reliable delivery and clear communication
Strong collaboration skills and ability to align stakeholders with different perspectives
Able to independently structure problems and break down complex challenges into actionable steps
Comfortable working in a fast-changing environment and adapting to evolving priorities, requirements, and business needs

Senior Data Scientist, Pistachio Team

Key skills