Data Scientist || 15 + Years experience

Role: Data Scientist

Location: San Jose, CA

Responsibilities

• Design and build end-to-end ML/data pipelines (ingestion transformation labeling feature engineering training validation deployment).
• Develop reproducible ML research workflows using Jupyter/Colab and version-controlled environments.
• Define and manage data labeling strategy (guidelines, quality checks, automation).
• Perform exploratory data analysis (EDA) and create datasets for supervised & unsupervised ML.
• Train, evaluate, and optimize ML models across environments (dev, staging, prod).
• Apply MLOps best practices (CI/CD for ML, pipeline automation, monitoring model drift, experiment tracking).
• Collaborate with ML engineers, software developers, and product managers to deliver production-ready ML solutions.

Requirements

• PhD in Computer Science, Data Science, Statistics, Applied Math, or related field.
• 3 years applied research/industry experience in ML or Data Science.
• Proven expertise in end-to-end ML pipeline design and deployment.
• Strong Python skills (NumPy, Pandas, scikit-learn, TensorFlow/PyTorch).
• Proficiency in SQL and large-scale data processing.
• Experience with MLOps tools (MLflow, Kubeflow, Airflow, Vertex AI, SageMaker).
• Familiarity with cloud platforms (Google Cloud Platform preferred) and Docker/Kubernetes.
• Experience automating data labeling workflows (active learning, weak supervision).

Nice-to-have: Ex-Google or top-tier tech company background.

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USA | Canada | UK | India