Company Overview

Our client is an organization operating within the BPO industry, focused on providing tech solutions for its clients. The company serves North American, European, and APAC regions and is committed to delivering quality solutions, operational excellence, and sustainable business growth. Additional information about the organization will be shared with selected candidates at the appropriate stage of the recruitment process.

Location: Taguig, Philippines

Work Setup: Hybrid, 3 Days WFH and 2 Days Onsite

Compensation Flexibility: Open to negotiation for highly qualified candidates.

Key Responsibilities

Research, design, develop, and deploy machine learning models and statistical algorithms to analyze, optimize, and improve the reliability of subsea fiber optic infrastructure.
Lead R&D initiatives involving predictive analytics, anomaly detection, subsea route optimization, risk modeling, and infrastructure reliability.
Conduct advanced geospatial analyses to support subsea cable route planning, monitoring, and optimization using spatial data frameworks and mapping tools.
Develop geospatial data models, analytical workflows, dashboards, and visualizations to communicate geographic, environmental, and infrastructure insights to technical and business stakeholders.
Design, build, and maintain scalable data pipelines and ETL/ELT workflows for ingesting, transforming, validating, and processing large-scale structured and unstructured datasets.
Integrate geospatial intelligence capabilities into machine learning models and analytical pipelines while ensuring data quality, integrity, and processing efficiency.
Leverage Large Language Models (LLMs) and generative AI to automate research, data extraction, knowledge discovery, analysis, and internal operational workflows.
Develop intelligent systems combining traditional machine learning with LLM-based capabilities, including prompt engineering, retrieval-augmented generation (RAG), and AI-assisted knowledge extraction.
Build and maintain internal tools, web applications, REST APIs, command-line utilities, and automation scripts to improve engineering and R&D processes.
Develop lightweight analytical applications using frameworks such as Streamlit, FastAPI, or Flask, following software engineering best practices for scalability, maintainability, and reusability.
Perform experimentation, model validation, benchmarking, testing, debugging, and performance optimization to ensure production readiness.
Collaborate with data scientists, software engineers, infrastructure specialists, and business stakeholders on technical strategy, solution architecture, and R&D initiatives.
Document technical designs, analytical methodologies, workflows, and implementation details, and communicate findings to technical and non-technical audiences.

Required Qualifications

3–5 years of experience designing and deploying advanced algorithms, machine learning models, statistical techniques, and data pipelines for analytical and optimization use cases.
Strong experience developing and deploying machine learning models and statistical frameworks in production environments.
Advanced proficiency in Python and its data science ecosystem, including NumPy, Pandas, and Scikit-learn, with experience using PyTorch or TensorFlow.
Hands-on experience with geospatial analysis, spatial data processing, and mapping tools such as GeoPandas, Google Earth Engine (GEE), and QGIS.
Experience architecting and maintaining scalable data pipelines for large-scale datasets, including data ingestion, transformation, validation, and processing.
Experience developing functional web applications using Streamlit, FastAPI, Flask, or similar frameworks.
Ability to develop REST APIs, command-line interface (CLI) utilities, and automation scripts for analytical, engineering, and research workflows.
Experience leveraging LLMs or generative AI technologies to automate processes, extract information, and generate insights from diverse data sources.
Strong analytical, statistical, and problem-solving skills, with the ability to evaluate model performance and translate complex data into actionable insights.
Strong communication and collaboration skills, with the ability to work across multidisciplinary technical teams and communicate findings to varied stakeholders.

Preferred Qualifications

Direct experience working with subsea fiber optic infrastructure, submarine cable networks, telecommunications infrastructure, or related engineering domains.
Experience applying geospatial intelligence and machine learning to subsea route planning, infrastructure monitoring, environmental analysis, risk assessment, or reliability optimization.
Familiarity with retrieval-augmented generation (RAG), prompt engineering, and AI-assisted knowledge extraction.
Experience integrating machine learning models, geospatial platforms, and LLM-based capabilities into production systems.
Familiarity with software testing, code reviews, deployment practices, technical documentation, and scalable application architecture.

Required Skills & Technologies

Programming: Python.
Data Science & Machine Learning: NumPy, Pandas, Scikit-learn, PyTorch, TensorFlow, statistical modeling, predictive analytics, anomaly detection, and model validation.
Geospatial Analytics: GeoPandas, Google Earth Engine (GEE), QGIS, spatial data modeling, mapping workflows, and geospatial visualization.
Data Engineering: Data pipelines, ETL/ELT, large-scale dataset processing, data validation, data quality management, and storage optimization.
AI & LLMs: Large Language Models, generative AI, prompt engineering, retrieval-augmented generation (RAG), and AI-assisted data extraction.
Application Development: Streamlit, FastAPI, Flask, REST APIs, web applications, CLI utilities, and automation scripts.
Infrastructure Analytics: Subsea route optimization, infrastructure monitoring, risk modeling, predictive analytics, and reliability analysis.
Software Engineering: Testing, debugging, code reviews, documentation, performance optimization, and maintainable software development.
Core Competencies: Research and development, statistical analysis, critical thinking, technical communication, cross-functional collaboration, and solution design.

About Paxsigna

PaxSigna is a specialist talent solutions division of the Lennor Group focused on Technology, Semiconductor & Electronics, and Advanced Engineering. We partner with startups, growth-stage businesses, and multinational enterprises to connect exceptional talent with transformative opportunities across highly specialized markets.

EQUAL OPPORTUNITY STATEMENT

PaxSigna is committed to fostering an inclusive and equitable recruitment process. All qualified applicants will receive consideration based on their qualifications, experience, capabilities, and business requirements.

DATA PRIVACY NOTICE

By submitting your application, you acknowledge that your personal information may be collected, processed, stored, and shared with authorized stakeholders solely for recruitment-related purposes in accordance with applicable data privacy laws and regulations.

LEGAL NOTICE

PaxSigna is a specialist talent solutions division of the Lennor Group. Recruitment and talent acquisition services are facilitated through Lennor Metier Consulting Philippines, Inc., the group's duly registered operating entity in the Philippines.

Senior Data Scientist - Hybrid