Staff Data Scientist - Artificial Intelligence

Description :

Role Overview :

Lead the design, development, and deployment of advanced machine learning and AI systems that drive measurable business impact. As a senior technical leader, you will define strategy, guide teams, and architect scalable, production-ready models that power innovation across the organization.

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.

Qualifications :

- Education : Masters or PhD in Computer Science, Data Science, Statistics, Mathematics, or a related quantitative field.

- Experience : 10+ years in data science, AI, or applied ML, including 3+ years in a senior or staff-level role leading impactful, production-level AI initiatives.

Required Technical Skills :

- 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.

Core Skills :

- Strong analytical and problem-solving ability with a focus on model interpretability, scalability, and measurable business impact.

- Proven ability to lead, mentor, and grow technical teams.

- Excellent communication and storytelling skills for cross-functional and executive engagement.