Enterprise Data Scientist

REFINITIV ASIA PTE. LTD.; Singapore; On-site; SGD 180,000 - 260,000; Full time

Job summary

Refinitiv Asia PTE. LTD. seeks an experienced Enterprise Data Scientist to lead AI/ML/NLP initiatives across the APAC region. You will design and deploy agentic AI systems, build POCs, and integrate with client workflows leveraging cloud platforms.

You will guide senior stakeholders, mentor teams in Singapore and wider APAC, and ensure governance and responsible AI practices align with regulatory expectations.

Qualifications

• 10+ years of experience in data science or related field focusing on AI/ML/NLP, preferably senior/lead.
• Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or related field; PhD a plus.
• Expertise in NLP and Generative AI with knowledge of LLMs and transformer architectures.
• Hands-on experience building agentic AI systems and multi-agent orchestration.
• Practical experience with RAG, embeddings, hybrid search, and retrieval evaluation.
• Experience fine-tuning large models with PEFT/LoRA, quantization, distillation; LLMOps basics.

Responsibilities

• Lead and run customer engagements across APAC with AI/ML/NLP focus.
• Co-create solutions addressing customer needs from ideation to technical design.
• Present complex AI concepts clearly to diverse stakeholders.
• Manage stakeholders and translate requirements into actionable solutions.
• Oversee development of POCs and integration with customer workflows.
• Design and deploy AI/ML solutions aligned with client infrastructure.
• Drive adoption of advanced AI technologies for high-value outcomes.
• Plan scaling strategies using cloud platforms (Azure, AWS, GCP).
• Design and implement RAG pipelines and agentic AI systems.
• Establish LLMOps, guardrails, observability; ensure safe deployments.

Skills

AI & ML leadership

NLP & LLMs

Retrieval-Augmented Generation

LangGraph / AutoGen

Python & SQL

Cloud platforms

Data science workflow

Stakeholder management

LLMOps

Production systems

Education

Bachelor's/Master's in CS/DS

PhD a plus

Tools

PyTorch

TensorFlow

Hugging Face

JAX

Kafka / Spark

MongoDB / DynamoDB

Elasticsearch

Pinecone / Weaviate

Job 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). You will collaborate closely with cross-functional teams, delivering innovative solutions to customers in highly dynamic, data-intensive environments.

Role & Responsibilities:

• Lead and execute complex customer engagements across the Asia-Pacific region, utilizing specialized expertise in AI, Machine Learning, Generative AI, and NLP, including building POCs, agentic AI workflows, integrations, and deployments with customer workflows.

• Apply a combination of technical, product, and data science expertise to co-create solutions that address specific customer needs, including ideation, clarification, technical design, and documentation.

• Lead detailed customer presentations for complex technical propositions, focusing on explaining advanced data science concepts and AI/ML solutions in an accessible way.

• Manage relationships with internal and external stakeholders, ensuring that project and customer-specific technical requirements are captured, refined, and translated into actionable solutions.

• Oversee and contribute to the development of Proof of Concepts, ensuring integration with customer workflows and systems.

• Lead the technical design and implementation of AI and machine learning solutions that integrate with existing client infrastructure.

• Drive the adoption of advanced data science and AI technologies to deliver high-value solutions.

• Develop and present strategies for scaling AI solutions, utilizing cloud platforms (Azure, AWS, GCP) for production-ready deployments.

• Design and implementRetrieval-Augmented Generation (RAG)pipelines andagentic AIsystem that orchestrate multiple tools and models to solve customer problems.

• EstablishLLMOps practices, including evaluation, guardrails, and observability, to ensure safe, reliable, and responsible deployment of generative AI solutions in line with regulatory expectations.

• Lead and mentor junior team members across the Singapore and broader Asia-Pacific team, fostering a collaborative environment for continuous learning and technical growth.

Qualifications and Experience:

• 10+ years of experiencein data science or a related field, with a focus on AI, machine learning, and NLP, preferably in a senior technical or leadership role.

• Bachelor’s or Master’s degreein Computer Science, Engineering, Data Science, or related field. A Ph.D. in a relevant field is a plus.

• Expertise in Natural Language Processing (NLP) and Generative AIwith a deep understanding of the latest LLM landscape, including transformer-based architectures such as BERT and T5, and current frontier and open-weight models (e.g., GPT-5.x, Claude 4/5, Gemini 2.x/3.x, Llama 4, DeepSeek, Qwen) that are driving the evolution of NLP and agentic AI applications.

• Hands-on experience building agentic AI systems, including multi-agent orchestration (e.g., LangGraph, AutoGen, CrewAI), tool/function calling, and integration via theModel Context Protocol (MCP).

• Practical experience with Retrieval-Augmented Generation (RAG), including chunking strategies, embedding models, hybrid search, and retrieval evaluation.

• Experience fine-tuning and adapting large models efficiently, using techniques such asLoRA/QLoRA, parameter-efficient fine-tuning (PEFT), quantization, and distillation, along withLLMOps practicesfor prompt evaluation, guardrails, hallucination testing, and observability (e.g., LangSmith, RAGAS, Arize).

• Awareness of responsible AI and governance requirements, including model risk management and emerging regulation (e.g., EU AI Act) as applicable to financial services.

• Extensive experiencewith advanced machine learning and deep learning frameworks such as PyTorch, TensorFlow, Hugging Face, and JAX for NLP, multimodal (vision-language), and other advanced AI tasks.

• Deep knowledge of cloud services (AWS, GCP, Azure)and their use in data science workflows, particularly for deploying machine learning models at scale.

• Expertise in Python, with advanced knowledge of modern data science and machine learning libraries such asPandas, NumPy, SciPy, scikit-learn, spaCy, as well as cutting-edge NLP frameworks likeHugging Face Transformers, Datasets, andNLTKfor efficient model training, fine-tuning, and data preprocessing.

• Strong programming skills inPython, R, and SQL, with advanced proficiency in handling large-scale data usingdistributed data systemslikeApache Spark,cloud-native NoSQL databasessuch asMongoDB,Cassandra, andDynamoDB, as well as search engines likeElasticsearchandvector databasesfor semantic search (e.g.,Pinecone,Weaviate).

• Hands-on experiencewith data ingestion, data wrangling, and data pipeline orchestration using tools likeApache Kafka,Apache Spark,Airflow, and distributed computing frameworks likeDaskandRay.

• Experience with advanced data science methodologies, includingensemble learning,deep reinforcement learning,transfer learning, and deployinglarge pre-trained modelsfor real-time inference and production.

• Ability to design, prototype, and deployNLP modelsfor a range of applications, from information retrieval to sentiment analysis, chatbots, and question answering systems.

• Demonstrated success in delivering solutions in complex, fast-paced environments with a focus on customer satisfaction and technical excellence.

• Strongcommunication skills, with the ability to explain complex technical concepts to both technical and non-technical stakeholders.

• Proven experience incustomer-facing rolesis highly valued, particularly in the enterprise tech or financial sectors, ideally serving customers acrossAsia-Pacific.

• Familiarity withAI-powered product developmentin industries such as finance, healthcare, or e-commerce.

• Experience withdata visualization toolslikeTableau,Power BI, orPlotlyto present data science findings effectively.

• Knowledge ofregulatory requirements in finance, including experience working with financial data feeds and APIs; familiarity with theSingapore regulatory environment (e.g., MAS)is a plus.

Equal Employment Opportunity:

As a global business, we embrace diversity of culture, background, and thought, recognizing it as a key to our success. We are an Equal Employment Opportunity Employer and offer a drug-free workplace.