Senior Data Scientist - AI / Machine Learning
Experience: 9+ years
Location: Bay Area - Open / Hybrid (as applicable)
Role Overview
We are seeking a Senior Data Scientist with deep expertise in Artificial Intelligence (AI) and Machine Learning (ML) to design, build, and deploy advanced data-driven and AI-powered solutions. This role requires strong hands-on experience across the full ML lifecycle-from problem framing and data engineering through model development, deployment, and monitoring-along with the ability to work independently and lead complex initiatives.
The ideal candidate combines strong statistical foundations, modern ML/GenAI capabilities, and production-grade engineering skills, and can partner effectively with business, engineering, and leadership stakeholders.
Key Responsibilities
- Lead end-to-end development of AI/ML solutions, including data exploration, feature engineering, model training, evaluation, and deployment
- Design, develop, and optimize machine learning models such as regression, classification, clustering, NLP, and deep learning models
- Build and deploy production-grade ML systems, ensuring scalability, performance, reliability, and cost efficiency
- Develop Generative AI solutions including LLM-based applications, prompt engineering, RAG pipelines, and agentic workflows (where applicable)
- Collaborate with data engineers to design and maintain robust data pipelines for structured and unstructured data
- Perform model validation, experimentation, and performance monitoring, ensuring accuracy, fairness, and robustness
- Translate complex analytical findings into clear business insights and recommendations for senior stakeholders
- Mentor junior data scientists and provide technical leadership across projects
- Contribute to AI governance, MLOps/LLMOps standards, documentation, and best practices
- Partner cross-functionally with product, engineering, and business teams to deliver measurable business outcomes
Required Qualifications
- 9+ years of hands-on experience in Data Science, Machine Learning, or Applied AI
- Strong proficiency in Python and common data science libraries (NumPy, pandas, scikit-learn)
- Solid experience with ML frameworks such as PyTorch, TensorFlow, or Hugging Face
- Strong understanding of statistics, probability, and experimental design
- Experience building and deploying models in cloud environments (AWS, Azure, or GCP)
- Hands-on experience with model deployment, monitoring, and MLOps tools (e.g., MLflow, CI/CD for ML)
- Experience working with large datasets, SQL, and modern data stores
- Excellent communication skills with the ability to explain technical concepts to non-technical audiences
Preferred / Nice-to-Have Skills
- Experience with Generative AI and Large Language Models (LLMs)
- Hands-on knowledge of RAG architectures, vector databases, and unstructured data pipelines
- Familiarity with LLMOps, observability, and responsible AI practices
- Experience in consulting or client-facing environments
- Knowledge of big data technologies (Spark, Databricks)
- Prior experience leading small teams or acting as a technical lead
Education
- Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related field
- PhD is a plus but not required