
Senior AI Data Scientist
4 days ago
We are seeking a highly skilled AI Transformation Specialist to join our team. This is a customer-facing, hands-on leadership role responsible for delivering end-to-end AI transformation starting from AI readiness assessments and data strategy to model development, intelligent agent deployment, and automation.
The ideal candidate will have consulting experience, excellent communication skills, and a strong background in data engineering and applied AI.
- Engage directly with customers to understand their business goals, current challenges, and workflow gaps.
- Conduct detailed discovery sessions to assess existing data infrastructure, sources, and readiness for AI.
- Identify AI opportunities and recommend tailored solutions aligned with the customer's use case.
- Design scalable data pipelines and AI-ready data layers while ensuring data quality and integrity.
- Develop and deploy AI/ML models and intelligent agents integrated with business operations.
- Ensure all solutions align with customers' data security, privacy, and compliance requirements.
- Collaborate with internal teams to ensure smooth delivery, adoption, and long-term success of AI solutions.
- Communicate technical solutions clearly to both technical and non-technical stakeholders.
Key Responsibilities:
- Achieve significant business value by driving AI innovation and adoption across various industries and sectors.
- Deliver high-quality AI solutions that meet or exceed customer expectations, resulting in improved efficiency, reduced costs, and enhanced decision-making capabilities.
- Lead cross-functional teams to develop and implement AI strategies that align with business objectives.
- Maintain up-to-date knowledge of emerging AI technologies, trends, and best practices to stay ahead in the industry.
Required Skills and Qualifications:
- 3+ years of experience in AI/data transformation roles at a consulting or technology services company.
- Proven experience in engaging enterprise clients and leading AI strategy and execution.
- Strong knowledge of data engineering, cloud data lakes, and modern AI/ML development workflows.
- Hands-on experience with Python, SQL, and ML frameworks like scikit-learn, TensorFlow, or PyTorch.
- Familiarity with LLMs, AI agent frameworks (e.g., LangChain, RAG), and vector databases (e.g., FAISS, Qdrant).
- Experience with cloud platforms like Azure, AWS, or GCP.
- Strong understanding of data security and regulatory compliance in solution design.
- Excellent communication and stakeholder management skills.
Bonus Points:
- Experience working with large-scale datasets and developing scalable AI solutions.
- Proficiency in cloud-based tools and platforms, such as Google Cloud AI Platform, Amazon SageMaker, or Microsoft Azure Machine Learning.
- Knowledge of DevOps practices and tools, such as Jenkins, Docker, or Kubernetes.
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