Senior Data Scientist

lamont global group services inc.; Philippines; On-site; PHP 900,000 - 1,500,000; Full time

Job summary

lamont global group services inc. is seeking a Senior Data Scientist / AI Engineer to turn data into actionable insights and build production-ready AI systems.

The role blends data science, ML, software engineering, and Generative AI to solve business challenges, deploying models and designing AI agents and multi-agent workflows.

You will work hands-on from data exploration to production, collaborating with product and engineering teams to deliver scalable AI features.

Qualifications

• 4+ years in Data Science, ML, or AI engineering.
• Proficient in Python and SQL; strong statistics and experimental methods.
• Hands-on with ML models deployment and modern AI frameworks (LLMs, Generative AI).

Responsibilities

• Analyze large and complex datasets to identify trends and opportunities.
• Build and evaluate predictive models, forecasting, personalization systems.
• Develop AI-powered product features using LLMs and Generative AI.
• Design RAG systems using embeddings and vector databases.
• Deploy ML models into production and monitor performance.

Skills

Python

SQL

Statistics

ML Engineering

Pandas

NumPy

PyTorch

TensorFlow

LLMs

Generative AI

Embeddings

Semantic search

Tool calling

LLM evaluation

AI agents

Multi-agent workflows

APIs

AWS

Docker

Git

CI/CD

Production deployment

Problem solving

Tools

Python

Job description

We are looking for a highly skilled Senior Data Scientist / AI Engineer to help transform data into actionable insights while building intelligent, production-ready AI systems.

This is not a traditional Data Scientist role. We are looking for someone who can combine data science, machine learning, software engineering, and modern Generative AI to solve complex business and product challenges. The role involves analyzing data, building predictive and machine learning models, developing AI-powered product features, and designing intelligent systems powered by LLMs, RAG, AI agents, and multi-agent workflows.

The ideal candidate is hands‑on, highly technical, and comfortable taking an idea from data exploration and experimentation through production deployment.

KEY RESPONSIBILITIES

Data Science & Machine Learning

• Analyze large and complex datasets to identify trends, patterns, insights, and business opportunities.
• Build predictive models, forecasting models, recommendation systems, personalization solutions, and other machine learning applications.
• Apply statistical analysis and experimentation to support product and business decision-making.
• Develop, evaluate, and improve machine learning models for accuracy, performance, scalability, and reliability.
• Work with product and engineering teams to identify opportunities where data and AI can create meaningful product improvements.
• Design and build AI-powered product features using LLMs and Generative AI.
• Develop RAG (Retrieval-Augmented Generation) systems using embeddings and vector databases.
• Build AI workflows using structured outputs, prompt engineering, tool/function calling, and external APIs.
• Design and develop AI agents capable of reasoning, planning, executing tasks, and interacting with tools and systems.
• Build multi-agent workflows and autonomous AI systems that enable collaboration between specialized AI agents.
• Explore and implement modern AI frameworks, tools, and architectures to solve real-world business and engineering problems.
• Develop and maintain data pipelines, ML services, and AI/ML APIs.
• Deploy machine learning and AI systems into production environments.
• Build scalable and maintainable AI applications using modern software engineering practices.
• Monitor and continuously improve model quality, latency, reliability, scalability, and operational cost.
• Implement model evaluation, observability, testing, and monitoring practices.
• Collaborate closely with Engineering and Product teams to integrate AI capabilities into production products and workflows.

REQUIRED QUALIFICATIONS

• 4+ years of experience in Data Science, Machine Learning, AI Engineering, or related technical roles.
• Strong proficiency in Python and SQL.
• Strong understanding of statistics, machine learning, data analysis, and experimental methods.
• Hands‑on experience with libraries such as Pandas, NumPy, scikit‑learn, PyTorch, and/or TensorFlow.
• Experience building, training, evaluating, and deploying machine learning models into production.
• Strong understanding of modern LLMs and Generative AI.
• Experience with:
  • o Embeddings and semantic search
  • o Structured outputs
  • o Tool/function calling
  • o LLM evaluation and optimization
• Experience building AI agents and agentic workflows.
• Familiarity with multi‑agent architectures and autonomous AI systems.
• Experience building APIs and integrating third‑party services and AI models.
• Familiarity with AWS or other cloud platforms, Docker, Git, CI/CD, and modern software development practices.
• Strong problem-solving skills and the ability to work independently in a fast‑paced environment.

PREFERRED QUALIFICATIONS

Experience with one or more of the following is highly preferred:

• Recommendation and personalization systems.
• User behavior analytics and product analytics.
• NLP and Generative AI applications.
• LangGraph, OpenAI Agents SDK, CrewAI, AutoGen, or similar agent frameworks.
• Vector databases such as Pinecone, Weaviate, Milvus, pgvector, or similar technologies.
• MLOps, model evaluation, monitoring, observability, and experimentation platforms.
• Distributed data processing and large‑scale data pipelines.
• Experience working in a startup or fast‑moving product environment.

AI-First Mindset

We are building an AI‑first organization and are looking for someone who actively uses modern AI tools to improve productivity, accelerate development, and solve complex problems.

The successful candidate should be excited about using AI not only to build product features, but also to help create intelligent systems that can:

• Automate complex business and engineering workflows.
• Enable AI agents to collaborate as specialized autonomous teams.
• Assist employees and engineering teams in completing complex tasks.
• Continuously improve workflows, decision‑making, and operational efficiency.
• Explore new opportunities for applying AI across the organization.

We value engineers and data scientists who are curious, experimental, pragmatic, and deeply hands‑on—people who can move quickly from an idea or problem to a working solution.

AI Development Tools

Candidates should be comfortable using modern AI‑assisted development tools to accelerate research, analysis, coding, experimentation, and delivery, including tools such as:

• Other modern AI development and productivity tools