Role: Data Scientist - Director
Location: Remote
Experience: 10-15 Years
Key Responsibilities:
- Strategic Leadership: Define and execute the company's data science and AI roadmap. Provide direction on model development, deployment, and long-term AI capability building.
- Model Development: Architect and deliver predictive, generative, and prescriptive models using advanced machine learning and deep learning techniques.
- AI Platform Engineering: Oversee end-to-end ML pipelines, from data collection and preprocessing to deployment and monitoring in production environments.
- Data Architecture: Ensure data integrity, scalability, and reproducibility across large and complex datasets.
- Mentorship: Build and mentor a high-performing team of data scientists and ML engineers. Promote best practices in experimentation, validation, and continuous learning.
- Innovation: Explore and apply emerging AI methods such as large language models (LLMs), multimodal learning, and reinforcement learning to real-world business problems.
- Stakeholder Engagement: Present analytical insights and model outcomes clearly and persuasively to technical and executive audiences.
Required Skills:
- Education: Master's or PhD in Computer Science, Data Science, Statistics, Mathematics, or a related quantitative field
- Expert proficiency in Python and frameworks such as TensorFlow, PyTorch, and scikit-learn.
- Strong foundation in statistical modeling, feature engineering, and end-to-end ML pipeline design.
- Proficiency in SQL and experience with data pipeline orchestration (Airflow, Dataflow, Kubeflow).
- Deep understanding of MLOps, including CI/CD for ML, model serving, and monitoring.
- Familiarity with big data technologies (Spark, Hadoop) and data visualization tools (Tableau, Power BI, Matplotlib).
- Preference for experience or certification with Google Cloud Platform (GCP), including BigQuery, Vertex AI, and Dataflow.
