22 дня назад
Data Scientist Data Scientist
Вакансия из Hirify Global, списка международных tech-компанийДля мэтча и отклика нужен Plus
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Data Scientist Data Scientist (Python/SQL/ML Operations): Applying and scaling modelling technology across messy customer datasets to deliver reliable production model outputs with an accent on statistical validation, diagnostics, automation, and observability. Focus on monitoring model quality, investigating data and implementation issues, building reusable tests and workflows, and improving production reliability across customer deployments.
Location: Melbourne or Sydney, Australia
Company
is an AI-powered growth platform that helps marketers measure media impact and make better investment decisions through its GrowthOS product.
What you will do
- Apply modelling technology to new and refreshed customer datasets.
- Monitor model inputs, outputs, performance, anomalies, drift, and emerging quality risks in production.
- Diagnose issues across data, configuration, implementation, and modelling methodology.
- Build reusable data checks, model tests, exploratory workflows, diagnostics, visualisations, monitoring, and alerts.
- Partner with Data Science and Engineering on feature engineering, validation, data access, automation, monitoring, and production reliability.
- Improve peer review, documentation, quality standards, and communication of technical findings and uncertainty.
Requirements
- Experience in data science, applied statistics, analytics, ML operations, or a related field.
- Strong foundations in statistical uncertainty, hypothesis testing, Bayesian reasoning, and common machine-learning approaches.
- Fluency in Python and SQL for exploring, transforming, and validating complex datasets.
- Experience writing maintainable, version-controlled code with tests and peer review.
- Ability to diagnose data, configuration, engineering, and modelling problems and work effectively with Data Science, Engineering, Product, and customer-facing teams.
- Understanding of production ML, including reliability, monitoring, failure recovery, and trusted model outputs.
Nice to have
- Experience with time-series modelling, causal inference, marketing analytics, GCP, dashboarding tools, or production ML systems.
- Experience with feature engineering, model development, or ML engineering.
Culture & Benefits
- Work within the Model Scale function, connecting modelling technology with real customer data and production delivery.
- Collaborate closely across Data Science, ML, software engineering, Product, and customer-facing teams.
- Contribute to shared documentation, standards, quality gates, and team knowledge.
- Opportunity to grow toward feature engineering, model development, or ML engineering.
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