234 Data Leadership jobs in the Philippines

• Collect, clean, and analyze large structured and unstructured datasets.
• Develop and deploy machine learning models to solve business challenges.
• Design and implement experiments to test hypotheses and measure outcomes.
• Build data pipelines and scalable solutions for data processing.
• Communicate insights and recommendations to technical and non-technical stakeholders.
• Collaborate with engineers, product managers, and business analysts to integrate data-driven solutions into products and processes.
• Stay updated on emerging tools, technologies, and best practices in data science.

At OnePuhunan (CreditAccess Philippines), we believe data is more than just numbers, it's the key to transforming lives and empowering communities. We're looking for a Data Science Officer who's passionate about using data, machine learning, and innovation to solve real-world challenges.

Why Join Us?

• Be part of a purpose-driven organization that impacts thousands of Filipino families

• Work on real business problems where your models and insights drive immediate results

• Collaborate with a dynamic and forward-thinking team that values innovation, agility, and growth

• Enjoy a culture that encourages continuous learning, creativity, and career development

What You'll Do

• Rapidly prototype, test, and deploy machine learning models that solve business challenges

• Clean, process, and optimize data for actionable insights and operational improvements

• Collaborate with stakeholders to design, refine, and validate models that deliver business impact

• Stay hands-on with SQL, Python, R, and other tools to ensure model accuracy and performance

• Build and scale advanced machine learning and artificial intelligence models to support business growth

• Develop interactive dashboards and data visualization tools for decision-making and performance tracking

• Design and implement AI solutions such as natural language processing, recommendation systems, and predictive analytics to enhance business operations

• Explore emerging AI technologies (e.g., generative AI, computer vision) and assess their application to financial inclusion

• Lead experimentation and model performance monitoring to ensure continuous improvement and reliability

What We're Looking For

• At least 5 years of experience in data science, machine learning, or advanced analytics

• Strong command of SQL, Python, and statistical modeling

• Background in Mathematics, Statistics, Economics, Computer Science, or related fields

• Analytical mindset, strong problem-solving skills, and the ability to communicate insights effectively

• A proactive team player who thrives in a fast-paced, impact-driven environment

Location

Head Office – Ortigas Center, Pasig City

Perks & Growth

• Work where data meets purpose, your contributions go beyond dashboards; they change lives

• Exposure to advanced analytics, big data tools, and innovation projects

• Opportunity to grow your career into leadership and product ownership roles

If you're ready to bring data to life and make an impact, apply now and be part of OnePuhunan's mission to empower communities through financial inclusion.

At Globe, our goal is to create a wonderful world for our people, business, and nation. By uniting people of passion who believe they can make a difference, we are confident that we can achieve this goal.

Job Description
Are you a data enthusiast with a passion for leading innovative projects and driving transformation in finance? Join our Finance AI task force as a Data Science Lead and spearhead our data analytics strategy. If you thrive on creating impactful solutions and mentoring a dynamic team, this role is for you

What You'll Do

• Lead and Innovate: Drive the development of RPA, analytical reports, and GPT workflows to support our Finance Division's RPA and AI initiatives.
• Collaborate: Work closely with Finance stakeholders to identify key questions and define impactful RPA and AI projects.
• Deliver Insights: Ensure the delivery of high-quality, actionable insights through rigorous RPA and AI data analysis.
• Mentor and Guide: Lead and mentor a team of data scientists, fostering a data-driven culture and promoting continuous learning in RPA and AI.
• Communicate Effectively: Present findings and recommendations related to RPA and AI to senior management and other stakeholders, making complex data understandable and actionable.
• Visual Storytelling: Utilize your storytelling and visualization skills to turn RPA and AI data insights into compelling narratives that drive business decisions.

What We're Looking For

• Educational Background: Bachelor's or Master's degree in Applied Mathematics, Data Science, Statistics, Computer Science, or a related field.
• Technical Expertise: Strong proficiency in Python and extensive experience in data visualization and storytelling, particularly with Looker Studio.
• Communication Skills: Excellent communication and presentation abilities, with the knack for translating complex data findings into clear, actionable business insights.
• Leadership Skills: Proven ability to lead, mentor, and inspire a team, fostering a culture of innovation and excellence.

Why You'll Love This Role

• Impactful Work: Lead projects that directly influence key business decisions and drive the success of our finance operations.
• Creative Freedom: Use your creativity to design innovative data solutions and compelling visualizations that make a real difference.
• Dynamic Team: Join a team of passionate, forward-thinking professionals who value collaboration and innovation.
• Career Growth: Enjoy continuous learning opportunities and professional development in the fast-evolving field of data analytics.
• Innovative Projects: Be part of exciting projects involving RPA and AI, pushing the boundaries of what's possible and shaping the future of finance automation.

Make Your Passion Part of Your Profession. Attracting the best and brightest Talents is pivotal to our success. If you are ready to share our purpose of Creating a Globe of Good, explore opportunities with us.

Who We Are:

At Kayana, we're shaping the future of technology by unlocking opportunities and driving progress at an accelerated pace. We push boundaries, expand horizons, and build on our legacy—supported by some of the country's most esteemed conglomerates and powered by the synergies of the MVP Group.

Our mission is clear: to create abundant opportunities and pave the way for generational progress for Filipinos. Harnessing the power of data and technology, we are leading the charge in crafting a new world where individuals and businesses are seamlessly connected to a digital universe, enabling them to do more and be more.

We're turning the impossible into possible. Sa Káyana, kaya na.

Job Summary:

The Data Science Associate will design, develop, and deploy machine learning models, generate actionable insights, and integrate external datasets (e.g., PSA, DOH, DOE) to strengthen analytics capabilities. This role is central to advancing Kayana's MLOps practices, ensuring models are scalable, reliable, and ethically applied.

The role also involves exploring emerging technologies such as Generative AI and LLMOps, building prototypes, and contributing to innovation initiatives. The associate may also mentor interns under Kayana's academic partnership programs.

Key Responsibilities:

• Model Development & Deployment - Build, train, and deploy predictive and generative ML models into production. Monitor, retrain, and optimize models to ensure fairness, scalability, and performance.

• Analytics & Insights – Extract and communicate insights from internal, public, and third-party datasets to support decision-making and product development.

• Data Enrichment – Acquire, integrate, and validate external data sources to improve model accuracy and analytical depth.

• MLOps & Automation – Implement best practices for versioning, monitoring, and retraining models. Contribute to strengthening Kayana's MLOps ecosystem.

• Innovation & Research – Explore and evaluate emerging tools, frameworks, and techniques in AI/ML, Generative AI, and MLOps. Deliver prototypes and proof-of-concepts for testing and adoption.

• Collaboration & Mentorship – Work closely with data engineers, product managers, and domain experts to deliver scalable solutions. Mentor interns and junior associates to build future talent pipelines.

Qualifications:

• Proven experience in developing and deploying ML models (e.g., classification, regression, clustering, forecasting)

• Strong programming skills in Python, with expertise in ML libraries such as scikit-learn, PyTorch, TensorFlow, Hugging Face.

• Familiarity with MLOps tools and practices (MLflow, Feast, CI/CD, model monitoring).

• Solid foundation in data engineering concepts, SQL, and cloud platforms (AWS, Databricks, Spark preferred).

• Experience integrating public or third-party datasets into analytical workflows.

• Understanding of ethical AI, model explainability, and bias detection.

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

Education:

• Bachelor's degree in Data Science, Computer Science, Statistics, Applied Mathematics, or a related field. Master's degree or equivalent experience in data science, machine learning, or AI is an advantage.

Preferred Skills:

• Strong programming in Python, PySpark, and SQL, with hands-on expertise in Databricks.

• Proficiency with BI tools such as Power BI, Metabase, or Superset for visualization and reporting.

• Experience in data warehouse modeling and analytics engineering practices.

• Knowledge of data lake architectures for large-scale data management.

• Proficiency with ML frameworks such as scikit-learn, LightGBM, XGBoost, CatBoost, TensorFlow, PyTorch, Hugging Face.

• Exposure to Generative AI frameworks (LangChain, LlamaIndex, vector databases)

• Hands-on experience with MLOps practices and tools (MLflow, Feast, CI/CD pipelines, monitoring)

• Familiarity with DataOps/orchestration tools (Airflow, Prefect, Dagster)

• Understanding of Medallion architecture (Bronze/Silver/Gold layers) and Feature Stores.

• Strong data storytelling, dashboarding, and visualization capabilities.

• Understanding of cloud platforms, especially AWS (SageMaker, S3, Redshift), will be an advantage.

• Understanding of big data computing (Spark clusters, distributed systems) and GPU acceleration for deep learning and Generative AI.

Data Science Engineer – NLP & LLMs

Full Time | Remote Setup

Are you passionate about building cutting-edge AI solutions? Do you have a strong foundation in Natural Language Processing (NLP), large language models (LLMs), and production-ready machine learning systems? Join our dynamic team of innovators and contribute to real-world projects that leverage the power of AI at scale.

• Research, design, and implement advanced NLP algorithms and core ML concepts.
• Develop and deploy deep learning models using PyTorch, TensorFlow, or Keras.
• Conduct rigorous experiments to evaluate model performance, optimize accuracy, and improve system efficiency.
• Apply prompt engineering techniques using Hugging Face and other state-of-the-art tools.
• Build and maintain scalable ML services using FastAPI and Kubernetes.
• Implement and optimize Retrieval-Augmented Generation (RAG) pipelines for LLM-based applications.

• Strong programming skills in Python.
• Solid experience with PyTorch, TensorFlow, and hands-on model tuning.
• Deep understanding of NLP fundamentals: text preprocessing, feature engineering, tokenization, and information retrieval.
• Working knowledge of LangChain, orchestration layers, and vector databases.
• Experience building pipelines with both locally hosted and externally hosted Large Language Models (LLMs).
• Proficient in scaling ML applications to production environments using containerized services.
• Familiarity with Computer Vision techniques and Frame-Per-Second (FPS) optimization is a plus.

• Bachelor's or Master's degree in Computer Science, AI, Data Science, or a related field.
• Experience with MLOps practices and versioning tools.
• Demonstrated success in delivering high-performing ML solutions in real-world use cases.

• Be part of a high-impact AI team working on state-of-the-art LLMs and NLP systems.
• Collaborate with passionate experts in machine learning, software engineering, and product innovation.
• Work in a fast-paced, agile environment that supports growth and experimentation.
• Enjoy a culture that values curiosity, technical excellence, and continuous learning.

COMPANY PROFILE: A global professional services company that provides a broad range of services and solutions in strategy, consulting, digital, technology, and operations.

Position: Data Science Consultant

Company Industry: Information Technology / Consulting Services

Work Location: Taguig

Work Schedule: Monday to Friday

Salary: Php 60,000-80,000 gross

Work Set Up: Hybrid

JOB REQUIREMENTS

• Minimum of 2 years' experience in Data Science or Machine Learning
• Proficient in Python and data analysis libraries (e.g., pandas, NumPy, scikit-learn)
• Experience implementing ML algorithms and data munging techniques
• Skilled in data visualization tools such as Tableau or Power BI.
• Strong analytical, problem-solving, and communication skills

JOB RESPONSIBILITIES:

• Define business problems and translate them into machine learning tasks
• Analyze and interpret complex datasets using ML techniques
• Develop predictive models to support business decisions
• Present insights and recommendations to stakeholders
• Collaborate with cross-functional teams to align data strategies with business goals

RECRUITMENT PROCESS (ONLINE)

• HR Interview
• Technical Assessment
• Hiring Manager Interview
• Job Offer

Job Types: Full-time, Permanent

Pay: Php60, Php80,000.00 per month

Benefits:

• Company events
• Employee discount
• Health insurance
• Life insurance
• Opportunities for promotion
• Pay raise
• Promotion to permanent employee

Work Location: In person

JOB TITLE: FINANCIAL DATA ANALYST

Job Summary

• The Financial Data Analyst will apply advanced data science and analytical techniques to support the Finance Department in making data-driven decisions. The role focuses on transforming financial and operational data into actionable insights that enhance forecasting, reporting, and overall business performance.

Key Responsibilities

• Collect, clean, and analyze large and complex financial datasets to identify trends, variances, and business opportunities.
• Develop and implement financial models, predictive analytics, and forecasting tools to support strategic planning and decision-making.
• Create dashboards, reports, and visualizations that communicate insights to finance leaders and cross-functional teams.
• Partner with finance and business units to translate analytical findings into actionable strategies and recommendations.
• Monitor financial performance indicators, identify risks, and propose data-driven solutions for efficiency and cost optimization.
• Ensure accuracy, integrity, and timeliness of financial data used in reports and analysis.

Job Qualifications:

• Degree in Data Science
• Fresh Graduate is encouraged to apply.
• Candidate must be willing to work onsite at MOA Complex, Pasay City.

Are you passionate about building cutting-edge AI solutions? Do you have a strong foundation in Natural Language Processing (NLP), large language models (LLMs), and production-ready machine learning systems? Join our dynamic team of innovators and contribute to real-world projects that leverage the power of AI at scale.

Key Responsibilities

• Research, design, and implement advanced NLP algorithms and core ML concepts.
• Develop and deploy deep learning models using PyTorch, TensorFlow, or Keras.
• Conduct rigorous experiments to evaluate model performance, optimize accuracy, and improve system efficiency.
• Apply prompt engineering techniques using Hugging Face and other state-of-the-art tools.
• Build and maintain scalable ML services using FastAPI and Kubernetes.
• Implement and optimize Retrieval-Augmented Generation (RAG) pipelines for LLM-based applications.

Your Expertise

• Strong programming skills in Python.
• Solid experience with PyTorch, TensorFlow, and hands-on model tuning.
• Deep understanding of NLP fundamentals: text preprocessing, feature engineering, tokenization, and information retrieval.
• Working knowledge of LangChain, orchestration layers, and vector databases.
• Experience building pipelines with both locally hosted and externally hosted Large Language Models (LLMs).
• Proficient in scaling ML applications to production environments using containerized services.
• Familiarity with Computer Vision techniques and Frame-Per-Second (FPS) optimization is a plus.

Preferred Qualifications

• Bachelor's or Master's degree in Computer Science, AI, Data Science, or a related field.
• Experience with MLOps practices and versioning tools.
• Demonstrated success in delivering high-performing ML solutions in real-world use cases.

Why Join Us?

• Be part of a high-impact AI team working on state-of-the-art LLMs and NLP systems.
• Collaborate with passionate experts in machine learning, software engineering, and product innovation.
• Work in a fast-paced, agile environment that supports growth and experimentation.
• Enjoy a culture that values curiosity, technical excellence, and continuous learning.

Job Type: Full-time

Pay: Php90, Php100,000.00 per month

Benefits:

• Additional leave
• Company Christmas gift
• Flextime
• Health insurance
• Life insurance
• Opportunities for promotion
• Paid training
• Pay raise
• Staff meals provided
• Work from home

Work Location: Remote

Department:
Project Services

Employment Type:
Permanent - Full Time

Location:
Manila

Description
Data Science Analysts investigate, develop, implement, and deploy a range of statistical and predictive solutions to benefit our clients in a variety of industries to help them answer their business challenges. In addition to the execution of various projects, this role also acts as an analytics consultant to both internal project teams and clients by translating data analysis and modeling into tactical and strategic insights that are clear, accurate, understandable, and applicable to decision making.

This is done using an array of tools, techniques, and frameworks that vary depending on the type of analysis being conducted. The four major types of analytics include:
descriptive analytics
(looks at data to examine, understand, and describe something that's already happened),
diagnostic analytics
(goes deeper than descriptive analytics by seeking to understand the why behind what happened),
predictive analytics
(relies on historical data, past trends, and assumptions to answer questions about what will happen in the future),
prescriptive analytics
(aims to identify specific actions that an individual or organization should take to reach future targets).

Responsibilities
Advanced statistical analysis

• Responsible for mining large data sets, executing statistical modeling and machine learning techniques, leading data interpretation and visualization of results to deliver insights
• Responsible for executing a variety of analyses such as: cluster analysis/segmentation, text analytics, customer lifetime value modeling, retention and survival models, portfolio analysis, propensity modeling, database scoring, clickstream data analysis, etc.
• Ensure that the method and analysis connect with the business challenge and overall project goals. Translate analysis into tactical and strategic insights
• Confidently guide clients and colleagues in understanding the insights derived from statistics and predictive techniques
• Skilled with data science programming in Python and SQL
• Stay up to date with emerging analytical techniques, demonstrating the ability to implement fresh thinking to create new value

Data handling

• An expert in using common technical tools to make the analyses / reporting more efficient through advanced usage of them (e.g., macros, syntaxes, etc.).
• Can organize any dataset in a usable format.
• Can design and implement automation on customized and complex trackers to ensure efficiency.
• Collaborate with seniors & experts to apply new technical skills (e.g., programming in different languages, developing new algorithms), techniques to accelerate computing and processing power of big data.

Data quality assurance

• Can propose out of the box solutions for any dataset.
• Collaborate with expert data engineers to correct data quality errors and enhance the data collection process.

Reporting & Visualization

• Can effectively communicate trends, patterns, and predictions based on relevant findings.

Account management

• Help in defining priorities for improving project execution on recurring accounts, either on ad hoc or structural projects (e.g., identify possibility to automate implementation, strengthen partnership with 3rd parties, etc.).

Method management

• Develop automation scripts for frequently implemented data processing and / or analysis techniques, that can be used cross projects.
• Collaborate with experts across departments in optimizing research methodologies and approaches.
• Can document innovation / new ways of conducting analysis.
• Can develop norms and processes to maintain it.

Technical knowledge

• An expert in all analytical and reporting software used.
• Has intermediate understanding and application of programming languages such as R, Python, Scala, Java, SQL, Julia, MATLAB.

Market Research Knowledge

• Has extensive market research knowledge and share expertise.
• Stay up to date with the industry trends and apply changes in own work.
• Share learnings within the team related to market research.

Marketing knowledge

• Has a genuine interest in marketing and brands.
• Has a basic understanding of the importance of marketing for organizations.

Language knowledge
Manage English at a professional level (verbal/ writing) and able to have a fluent and accurate conversation.

Qualifications

• Bachelor's or Master's degree in Statistics, Data Sciences, Economics, Operations Research, Applied Mathematics, Computer Science, or related field of study is desirable
• 4+ years of experience in data science and advanced modeling (such as statistical, econometric, optimization, machine/deep learning)