Senior Data Analyst - Hybrid

Our brand, Lennor Metier Consulting, a DOLE-licensed headhunting and recruitment agency in the Philippines, is proud to partner with a multinational tech company in their search for a Senior Data Analyst based in BGC.

Salary Range: Open

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

Shift Schedule: Day Shift

Location: Taguig City

The Role

We are seeking a highly analytical and technically advanced Data Analyst to drive innovation in subsea fiber optic infrastructure analytics and intelligent automation. This role will focus on the research, design, and deployment of machine learning algorithms, geospatial intelligence solutions, and data-driven systems that improve the performance, monitoring, optimization, and reliability of subsea cable networks.

The ideal candidate combines strong expertise in machine learning, geospatial analysis, software engineering, and data engineering, with the ability to build scalable internal tools and automation frameworks that support advanced R&D initiatives.

Your Responsibilities

• Research & Algorithm Development
• Design, develop, and deploy advanced machine learning models and statistical algorithms for subsea fiber optic infrastructure analysis and optimization.
• Conduct R&D initiatives focused on predictive analytics, anomaly detection, route optimization, risk modeling, and infrastructure reliability.
• Build scalable analytical frameworks that process and interpret large volumes of structured and unstructured data.
• Evaluate emerging AI/ML methodologies and identify opportunities for innovation and operational improvement.
• Perform experimentation, model validation, benchmarking, and performance optimization for production-grade solutions.
• Geospatial Intelligence & Spatial Analytics
• Perform advanced geospatial analysis to support subsea route planning, monitoring, and optimization initiatives.
• Develop spatial data models and mapping workflows using geospatial libraries and platforms.
• Create high-impact visualizations, dashboards, and geospatial insights for technical and business stakeholders.
• Analyze geographic, environmental, and infrastructure datasets to identify patterns, risks, and operational opportunities.
• Integrate GIS and spatial intelligence capabilities into machine learning and analytics pipelines.
• Data Engineering & Pipeline Development
• Architect and maintain scalable data pipelines for ingesting, transforming, validating, and processing large-scale datasets.
• Build efficient ETL/ELT workflows supporting machine learning and geospatial analytics initiatives.
• Optimize data storage, retrieval, and processing for high-volume analytical workloads.
• Ensure data quality, integrity, consistency, and reliability across systems and pipelines.
• AI & LLM Integration
• Leverage Large Language Models (LLMs) and generative AI technologies to automate research, data extraction, analysis, and operational workflows.
• Develop intelligent systems that combine traditional machine learning with LLM-based capabilities. Integrate AI-driven automation into internal platforms, analytics tools, and R&D workflows.
• Explore prompt engineering, retrieval-augmented generation (RAG), and AI-assisted knowledge extraction techniques.
• Software Development & Tooling
• Design and develop internal tools, web applications, APIs, and automation utilities to streamline engineering and R&D processes.
• Build lightweight web applications and analytical interfaces using frameworks such as Streamlit, FastAPI, or Flask.
• Develop command-line tools (CLI utilities) and automation scripts for operational and research use cases.
• Create reusable, maintainable, and scalable software components following engineering best practices.
• Participate in code reviews, testing, debugging, documentation, and deployment activities.
• Collaboration & Stakeholder Engagement
• Work closely with data scientists, software engineers, infrastructure specialists, and business stakeholders to deliver innovative technical solutions.
• Translate complex analytical findings into actionable insights and presentations for both technical and non-technical audiences.
• Contribute to technical strategy, architecture discussions, and long-term R&D planning.
• Document methodologies, technical designs, workflows, and implementation details.
  

• R&D & Algorithmic Development: Must have 3-5 years of experience in designing and deploying sophisticated algorithms and data pipelines using machine learning and statistical techniques to enhance the performance and reliability of subsea fiber optic infrastructure.
• Geospatial Intelligence: Experience in conducting advanced geospatial analyses to map, monitor, and optimize subsea routes. Deliver high-impact visualizations and insights to stakeholders using spatial data frameworks.
• Technical Proficiency: Advanced expertise in Python and its data science ecosystem (NumPy, Pandas, Scikit-Learn, PyTorch, or TensorFlow).
• Geospatial Expertise: Strong experience with geospatial analysis tools and platforms such as Geopandas, Google Earth Engine (GEE) and QGIS.
• Machine Learning & Statistics: Proven track record of developing and deploying ML models and statistical frameworks in a production environment.
• Software Development: Experience building functional web applications (e.g., Streamlit, FastAPI, or Flask) and developing robust CLI utilities.
• Data Engineering: Ability to architect data pipelines and manage large-scale datasets for analytics.
• LLM Integration: Leverage Large Language Models (LLMs) to automate complex processes and extract insights from various sources of data.
• Tooling & Automation: Design and build custom internal tools, including web applications, REST APIs, CLI utilities, and automation scripts to streamline R&D workflows
  
  

• We kindly request your patience as we receive a significant number of applications. Rest assured that our team will update your applications status soon. In the meantime, we encourage you to follow our LinkedIn page to stay informed about future opportunities and company updates.