Description
As an Enterprise Data Scientist, you will leverage cutting-edge technologies and methodologies to deliver data-driven insights and solutions for complex customer needs.
You will work on end-to-end solutions, including building Proof of Concepts (POCs) and production-grade agentic AI systems, professional services, and integrating third-party technologies with client systems.
This role is pivotal to ensuring the successful implementation of data science-driven products and capabilities, with a key focus on AI, machine learning, generative AI, and Natural Language Processing (NLP).
Role & Responsibilities:
- Lead and execute complex customer engagements across the Asia-Pacific region, utilizing specialized expertise in AI, Machine Learning, Generative AI, and NLP.
- Apply a combination of technical, product, and data science expertise to co-create solutions that address specific customer needs.
- Lead detailed customer presentations for complex technical propositions.
- Manage relationships with internal and external stakeholders.
- Oversee and contribute to the development of Proof of Concepts.
- Lead the technical design and implementation of AI and machine learning solutions.
- Drive the adoption of advanced data science and AI technologies.
- Develop and present strategies for scaling AI solutions.
- Design and implement Retrieval-Augmented Generation (RAG) pipelines and agentic AI systems.
- Establish LLMOps practices.
- Lead and mentor junior team members.
Qualifications and Experience:
- 10+ years of experience in data science or a related field.
- Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or related field.
- Expertise in Natural Language Processing (NLP) and Generative AI.
- Hands-on experience building agentic AI systems.
- Practical experience with Retrieval-Augmented Generation (RAG).
- Experience fine-tuning and adapting large models efficiently.
- Awareness of responsible AI and governance requirements.
- Extensive experience with advanced machine learning and deep learning frameworks.
- Deep knowledge of cloud services.
- Expertise in Python.
- Strong programming skills in Python, R, and SQL.
- Hands-on experience with data ingestion, data wrangling, and data pipeline orchestration.
- Experience with advanced data science methodologies.
- Ability to design, prototype, and deploy NLP models.
- Demonstrated success in delivering solutions in complex, fast-paced environments.
- Strong communication skills.
- Proven experience in customer-facing roles.
- Familiarity with AI-powered product development.
- Experience with data visualization tools.
- Knowledge of regulatory requirements in finance.