Senior Data Scientist (AI)

Location: Hybrid, Manila, Philippines

Company

hirify.global’s Enterprise Data Group develops data science solutions for governance, risk, transparency, fintech, automation, business intelligence, data governance, and generative AI initiatives.

What you will do

• Design, implement, evaluate, and fine-tune traditional ML, deep learning, NLP, and LLM/GenAI solutions.
• Build prompt strategies, evaluation frameworks, guardrails, RAG systems, and transformer-based models.
• Engineer scalable Databricks data and ML pipelines using PySpark, Delta Lake, and MLflow.
• Deploy, monitor, and maintain production models on Azure, including CI/CD, versioning, and drift detection.
• Validate model inputs, outputs, testing practices, and business impact across structured, unstructured, and semi-structured data.
• Partner with engineering, product, business, senior leadership, and clients while mentoring junior data scientists and contributing to responsible AI standards.

Requirements

• Advanced degree (MS or PhD) in computer science, statistics, mathematics, analytics, or a related quantitative field.
• 5+ years of applied machine learning experience, including delivering models to production.
• Strong Python skills and experience with scikit-learn, PyTorch or TensorFlow, pandas, and Hugging Face Transformers.
• Hands-on Databricks experience, including notebooks, jobs, MLflow, and Unity Catalog, plus Spark/PySpark.
• Production Azure experience, ideally including Azure AI Foundry, Azure OpenAI Service, and Azure Data Lake.
• Experience across traditional/statistical ML, deep learning, NLP, and LLM/GenAI, including prompt engineering, RAG, embeddings, vector databases, evaluation, and agentic workflows.
• Experience across the full ML lifecycle: data validation, feature engineering, model design, experimentation, deployment, and monitoring.
• Experience with structured and unstructured data, including text, documents, and semi-structured sources.
• Strong statistical reasoning about uncertainty, bias, and model risk, plus excellent technical and business communication skills.

Nice to have

• Experience in financial services, risk, compliance, or regulatory domains.
• Familiarity with MLOps tooling such as Docker, Kubernetes, Azure DevOps, or GitHub Actions.
• Experience with LangChain, LlamaIndex, Semantic Kernel, LLM evaluation tooling, and production GenAI deployment.
• Knowledge of responsible AI, including fairness, explainability, and data privacy.

Culture & Benefits

• Collaboration with data science and engineering professionals and stakeholders from financial institutions, law enforcement agencies, and government bodies.
• Work in a hybrid setup as part of One hirify.global and contribute to team standards for code quality, experimentation, and responsible AI.