Job description
AuroraData Systems is a fast-growing tech company focusing on AI-driven analytics for enterprise clients. We are seeking a Data Scientist to join our Seattle team to build scalable models, generate actionable insights, and influence product strategy.
As a member of our data science team, you will collaborate with product, engineering, and analytics to deploy end-to-end solutions from data collection to model deployment, monitoring, and iteration.
Responsibility
- Design and implement machine learning models to solve business problems across product, marketing, and operations.
- Engineer robust data pipelines and feature stores to enable scalable analytics.
- Collaborate with product and engineering to translate requirements into data science solutions.
- Validate models with rigorous experimentation, cross-validation, and robust evaluation.
- Deploy models to production; monitor performance and drift; iterate to improve results.
- Create compelling data visualizations and present insights to stakeholders to influence decision making.
- Stay current with advances in ML, AI, and data engineering, and contribute to internal playbooks and best practices.
Qualification
- Master's degree or PhD in Data Science, Computer Science, Statistics, or a related field.
- 3+ years of hands-on data science experience in industry or equivalent.
- Proficiency in Python (pandas, scikit-learn, numpy) and SQL; experience with Spark or Hadoop is a plus.
- Strong knowledge of ML algorithms, including regression, classification, tree-based methods, NLP, and time-series.
- Experience with model deployment and MLOps concepts (Docker, MLflow, CI/CD, monitoring).
- Excellent communication skills and ability to explain complex results to non-technical audiences.
- Experience with cloud platforms (AWS, GCP, or Azure) and data visualization tools.