We are hiring multiple Data Scientists across Junior, Mid-Level, and Senior levels to join a global financial technology and data organization.

The team develops data-driven, AI and machine learning solutions that transform large volumes of financial and business data into intelligent products and services. You will work closely with Data, Technology, Product, and business teams to develop solutions across Machine Learning, NLP, LLMs, RAG, data pipelines, and AI/ML platforms.

Depending on your level, you will contribute to, independently deliver, or lead the development of production-grade AI and data solutions.

Key Responsibilities

• Develop and maintain data acquisition, cleaning, transformation, and processing workflows for structured and unstructured data.

• Build, train, test, validate, and deploy machine learning and deep learning models for business and financial applications.

• Develop solutions using NLP, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and other AI technologies.

• Work with large and complex datasets, including financial documents, web data, PDFs, and other structured and unstructured sources.

• Develop capabilities for web scraping/crawling, entity extraction, document processing, and data transformation.

• Design and implement data and ML pipelines using cloud technologies such as AWS, Azure, or GCP.

• Apply MLOps and CI/CD practices to support reliable deployment, monitoring, and maintenance of ML/AI solutions.

• Develop evaluation frameworks, metrics, and testing approaches to assess the quality and performance of AI/ML solutions.

• Collaborate with Data Engineers, Software Engineers, Product Managers, and domain experts to translate business requirements into technical solutions.

• Communicate technical findings, project progress, and outcomes to technical and non-technical stakeholders.

• Stay up to date with emerging technologies and developments in AI, ML, NLP, and Generative AI.

Level Expectations

Junior Data Scientist

0–2 years of experience

• Support the development of data pipelines, ML models, and AI solutions.

• Perform data cleaning, transformation, feature engineering, and exploratory analysis.

• Assist with model development, testing, and evaluation.

• Gain exposure to NLP, LLMs, RAG, cloud technologies, and MLOps under the guidance of senior team members.

Data Scientist / Mid-Level

3–5 years of experience

• Independently develop and deliver ML/AI solutions from data preparation through deployment.

• Build and evaluate predictive, NLP, and Generative AI models.

• Contribute to production-grade data and ML platforms and pipelines.

• Work directly with business and technical stakeholders to translate requirements into scalable solutions.

Senior Data Scientist

6–8+ years of experience

• Lead the design and development of production-grade AI/ML solutions and data platforms.

• Own technical direction for complex AI/ML initiatives and contribute to product and technology roadmaps.

• Optimize models and solutions for accuracy, performance, scalability, and reliability.

• Provide technical leadership and influence engineering, product, and business stakeholders.

• Evaluate emerging and third-party AI technologies and establish best practices for AI/ML development and deployment.

Requirements

• Degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related quantitative/technical field.

• Strong programming experience in Python and SQL.

• Experience with Machine Learning, predictive modeling, feature engineering, and statistical analysis.

• Experience with one or more of NLP, Deep Learning, LLMs, Generative AI, or RAG.

• Experience with ML frameworks such as Scikit-learn, TensorFlow, or PyTorch.

• Experience working with large datasets and relational databases.

• Exposure to or experience with AWS, Azure, GCP, or other cloud platforms.

• Understanding of MLOps, CI/CD, model deployment, monitoring, and production ML systems.

• Experience with data processing, ETL/ELT, or data pipeline development is an advantage.

• Strong analytical, problem-solving, communication, and collaboration skills.

Preferred

• Experience in financial services, fintech, investment banking, financial markets, or financial data.

• Experience working with financial documents, news, research content, or other unstructured data.

• Experience with RAG frameworks, vector databases, embeddings, prompt engineering, AI agents, or LLM evaluation.

• Experience working in global or distributed teams.

Why Join?

You will have the opportunity to work on large-scale financial data and AI initiatives, leveraging technologies such as Machine Learning, Generative AI, LLMs, NLP, RAG, cloud platforms, and MLOps to build solutions used by professionals across the global financial industry.

Location: Taguig, Philippines
Work Arrangement: Hybrid
Shift: Mid Shift / Night Shift
Employment Type: Full-time
Openings: Multiple Headcounts

Due to the high volume of applications we are experiencing, our team will only be in touch with you if your application is shortlisted.