Job Description
Qualifications
Education & Experience
● Advanced degree (Masterʼs or PhD) in Data Science, Computer Science, Statistics, Mathematics, or a related quantitative field.
● 8–12 years of professional experience in data science, analytics, or machine learning, with a demonstrated ability to deliver projects from data ingestion & EDA through to production deployment and monitoring.
● Proven track record of building end-to-end solutions: data acquisition, feature engineering, model development, ML Ops deployment, monitoring, and iterative improvement.
● Hands-on expertise with cloud-based data platforms, particularly the Google Cloud stack (BigQuery for large-scale data warehousing and Vertex AI for ML lifecycle management).
● Experience with alternate ML platforms such as Alteryx, Databricks, H2O.ai, or equivalent tools that support rapid prototyping, automation, and scalable model deployment.
● ...
Education & Experience
● Advanced degree (Masterʼs or PhD) in Data Science, Computer Science, Statistics, Mathematics, or a related quantitative field.
● 8–12 years of professional experience in data science, analytics, or machine learning, with a demonstrated ability to deliver projects from data ingestion & EDA through to production deployment and monitoring.
● Proven track record of building end-to-end solutions: data acquisition, feature engineering, model development, ML Ops deployment, monitoring, and iterative improvement.
● Hands-on expertise with cloud-based data platforms, particularly the Google Cloud stack (BigQuery for large-scale data warehousing and Vertex AI for ML lifecycle management).
● Experience with alternate ML platforms such as Alteryx, Databricks, H2O.ai, or equivalent tools that support rapid prototyping, automation, and scalable model deployment.
● ...
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