Senior Data Scientist, Machine Learning & Gen AI
Overview
As Senior Data Scientist, you own advanced analytics and model development for a 10+ year track record in ML and DL. You join a Data Science team supporting MLOps in a hybrid environment. This role blends classical ML with Gen AI across Oracle, GCP, and AWS. You call on SQL to interrogate large datasets, then drive models from prototype to production, a role that defines your impact from day one.
What You'll Do8
- 1Build and deploy ML and Deep Learning models on GCP or AWS, using Python and SQL for data extraction.
- 2Design experiments for Gen AI solutions, integrating LLM and RAG patterns with traditional ML pipelines.
- 3Own data wrangling for Oracle and cloud datasets, translating raw tables into features for model training.
- 4Lead model evaluation and tuning, setting performance thresholds and validating against business metrics.
- 5Collaborate with MLOps engineers to containerize models with Docker and orchestrate with Kubernetes.
- 6Ship end-to-end analytics products from hypothesis to deployment, including monitoring and retraining loops.
- 7Drive migration of legacy ML workflows to modern Gen AI frameworks, documenting trade-offs.
- 8Debug pipeline failures in Spark and Airflow, optimizing query performance across BigQuery and Redshift.
Requirements8
- 110+ years in data science roles with hands-on Python and SQL.
- 25+ years building ML models in scikit-learn, TensorFlow, or PyTorch.
- 33+ years with Gen AI such as OpenAI GPT, Anthropic Claude, or open-source LLMs.
- 42+ years cloud experience on AWS or GCP, including S3, EC2, Lambda, or BigQuery.
- 5Proven ability to query Oracle on-prem and cloud databases.
- 61+ years supporting MLOps workflows with Docker, Kubernetes, or MLflow.
- 7Strong grasp of statistical methods, experimentation, and model validation.
- 8Experience with Git and version control in a collaborative team.
Salary Insight
Salary not disclosed in listing
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