Data Science Consultant (AI/ML)
Role details
Job location
Tech stack
Job description
- Deliver end-to-end Generative/Agentic AI solutions for enterprise customers, managing the full lifecycle from problem definition, data preparation, model development, deployment, and monitoring.
- Build custom AI/ML agents and applications, designing innovative, verticalized use cases across banking, finance, insurance, retail, healthcare, and manufacturing.
- Guide customers through their GenAI journey, focusing on LLM selection, evaluation, fine-tuning, prompt engineering, and building scalable GenAI/RAG pipelines tailored to specific business needs.
- Apply expertise in hybrid AI solutions, combining predictive AI algorithms (e.g., regression, time-series forecasting, anomaly detection) with Generative AI techniques.
- Conduct customer enablement programs, including hands-on training sessions, workshops, and hackathons, to boost AI adoption among technical and executive stakeholders.
- Translate complex technical outputs into clear business impact narratives, advising non-technical leaders on the value and risks of AI adoption.
- Collaborate with internal R&D teams to enhance the Company GenAI/ML technology stack and contribute to reusable assets, best practices, and industry accelerators.
Requirements
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5+ years of hands-on experience in data science, machine learning, and AI, with a proven track record of delivering projects for enterprise customers.
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Strong expertise in LLMs and GenAI: practical experience with fine-tuning, evaluation, RAG design, LLMOps, guardrails, and building domain-specific custom LLM solutions.
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Experience with a wide range of predictive AI algorithms (e.g., GLMs, Random Forest, Gradient Boosting, Neural Networks, NLP, time-series forecasting).
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Demonstrated ability to design and deliver training, workshops, and customer enablement programs for diverse stakeholders.
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Hands-on experience or demonstrably similar advanced AutoML/ML platforms.
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Proficiency in Python (preferred) and industry-standard data science/ML libraries and frameworks.
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Familiarity with MLOps and production monitoring tools.
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Excellent customer-facing and communication skills: proven ability to engage with and clearly articulate technical concepts to both technical and executive audiences.
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Strong problem-solving skills and the ability to work independently in dynamic, customer-driven environments.
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Singaporeans ONLY, * Prior experience in building AI/ML agents and Generative AI applications for specific industry use cases.
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Demonstrated thought leadership in AI (e.g., published technical blogs, conference talks, or significant open-source contributions).
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Experience leading AI hackathons, bootcamps, or innovation workshops with enterprise customers.
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Familiarity with the demands of enterprise-grade AI solutioning related to security, governance, scalability, and regulatory compliance.