160 Natural Language Processing jobs in the Philippines

The Role

• Own the development and implementation of data models, analytics frameworks, and experimentation strategies across the platform.
• Analyze user journeys and behavioral data across tenants to uncover insights that inform digital product development and engagement strategies.
• Develop segmentation and predictive models to support personalization and proactive member engagement based on demographics, behavior, and interaction activities etc.
• Design and analyze experiments (A/B testing, cohort studies) to assess feature effectiveness and improve user engagement.
• Collaborate closely with product managers, designers, and engineering to define KPIs, track product performance, and identify growth opportunities.
• Create dashboards and self-serve analytics tools to empower internal teams with real-time insights.
• Mentor and coach junior data team members, fostering their growth in analytics, modeling, and communication.
• Contribute to and uphold best practices in data quality, governance, and compliance, especially within the financial services sector.

The Requirements

• 10+ years of experience in data science, analytics, or related roles—ideally within fintech, pensions, insurance, or employee benefits domains.
• Strong SQL skills and experience working with large, complex data sets.
• Proficiency in SQL and Python or R, with hands-on experience in machine learning, predictive modeling, and statistical analysis.
• Proven experience working directly with product analytics platforms like Mixpanel, Amplitude, or similar tools.
• Experience with data visualization and BI tools (e.g., Looker, Power BI, Tableau).
• Solid grasp of statistics, experimentation design, and causal inference techniques.
• Excellent communication and stakeholder management skills—able to influence and align diverse teams.
• Demonstrated team leadership or people management experience.

WTW is an Equal Opportunity Employer

We are seeking a Data Scientist specializing in analytics and statistical analysis to join our AI Rater Incubation Program. This role is central to uncovering insights from rater-generated data and helping our client improve AI-driven ad relevance and related projects. You will analyze operational and labeling data to identify trends, surface bias, and design frameworks that strengthen both program performance and client outcomes.

This is a strategic role where you will design models, build analytics frameworks, and collaborate closely with linguists, program managers, and raters. Your insights will guide operational decisions, shape client recommendations, and drive innovation at the intersection of AI, linguistics, and human judgment.

Main Responsibilities:

• Develop, implement, and maintain program and rater performance metrics (e.g., quality, bias, consistency, efficiency).
• Design and analyze experiments and statistical tests to uncover drivers of performance and label patterns.
• Build dashboards, reports, and automated monitoring systems in Looker Studio, Sisense, or similar BI tools.
• Identify and highlight potential biases or preferences in labeling data (e.g., topic-specific or cultural/linguistic bias).
• Collaborate with linguists, raters, and program managers to translate findings into operational and client-facing insights.
• Conduct applied analytics using Python, SQL, and statistical modeling, with opportunities to apply predictive modeling, NLP, and bias detection algorithms.
• Manage and explore datasets ranging from structured spreadsheets/CSVs to larger-scale rater outputs (scaling to millions of rows as needed).
• Partner with client teams by supporting linguists and PMs in meetings where technical depth and context are required.
• Drive process improvements and automation, surfacing insights that reduce variability, improve efficiency, and strengthen program resilience.

Qualifications:

• Strong proficiency in Python, SQL and R
• Applied expertise in statistical modeling and experimental design (e.g., sampling, confidence intervals, agreement metrics).
• Experience working with moderate-to-large datasets, with ability to scale analyses as data volume grows.
• Familiarity with BI/visualization tools such as Looker Studio, Sisense, Tableau, or PowerBI.
• Experience in Google Cloud Platform (GCP) or other cloud data environments preferred.
• Excellent ability to communicate insights clearly through reports, dashboards, and presentations to both technical and non-technical stakeholders.
• Strong collaboration skills, with experience working in cross-functional teams (linguists, operations, engineering, client teams).
• Comfortable supporting client meetings as a subject-matter expert, while primarily focused on internal analysis and insights.

Preferred Skills

• Experience with bias detection, NLP, or applied AI/ML models.
• Knowledge of rater evaluation methods and quality metrics such as Krippendorff's alpha, chance-corrected agreement, or structured sampling.
• Background in quality, linguistic or cultural data analysis is a plus.
• Exposure to human computation programs or crowdsourced labeling workflows.

Studies & Experience:

• English B2
  - Required
  .
• Oral and written comprehension.
• Appropriate use of language.
• 3+ years in a quantitative role (Data Scientist, Product Analyst, or similar) with proven ability to navigate ambiguous environments.
• Bachelor's degree in Statistics, Mathematics, Computer Science, Economics, or a related field OR equivalent practical experience.
• An advanced degree is a plus but not required.

Benefits and Perks:

• Competitive salary, and benefits package.
• Opportunity to work at the intersection of AI, linguistics, and human judgment, driving impact in a rapidly evolving industry.
• Remote position
• Exposure to cutting-edge AI projects with a global client.
• Growth opportunities as the program scales.
• Annual merit increase based on performance.

We are seeking a highly skilled Data Scientist with expertise in statistical modeling, machine learning, and data analytics. The ideal candidate will be proficient in Python, experienced in working with large datasets, and capable of building predictive models that deliver actionable business insights. This role requires both strong technical expertise and the ability to communicate complex findings to diverse stakeholders.

KEY RESPONSIBILITIES

• Collect, clean, and analyze structured and unstructured datasets from multiple sources.
• Develop, train, and evaluate statistical and machine learning models to solve business problems.
• Apply advanced analytics to uncover trends, patterns, and insights that inform decision-making.
• Collaborate with engineering and product teams to deploy models into production environments.
• Create clear visualizations, reports, and presentations to communicate results effectively to both technical and non-technical stakeholders.

• Bachelor's or Master's degree in Data Science, Statistics, Computer Science, or a related field (PhD is a plus).
• Proven experience in data analysis, feature engineering, and machine learning model development.
• Proficiency in Python, SQL, and key data science libraries (Pandas, NumPy, Scikit-learn, etc.).
• Strong foundation in statistics, hypothesis testing, and model evaluation techniques.
• Familiarity with big data tools (Spark, Hadoop) and data visualization tools (Tableau, Power BI, Matplotlib, Seaborn) is a strong plus.
• Excellent problem-solving skills and ability to work cross-functionally in a fast-paced environment.

The Data Scientist plays a crucial role in advancing RAFI Microfinance's data-driven decision-making culture. This role is responsible for designing, prototyping, testing, and implementing advanced analytics solutions that support organizational strategies and business needs. The Data Scientist extracts, integrates, and explores data from multiple sources, applies statistical and machine learning methods, and develops predictive and prescriptive models to uncover business value.

Beyond technical execution, the role requires the ability to communicate insights effectively, influence stakeholders, and ensure solutions are scalable and aligned with compliance standards. The Data Scientist contributes to innovation, efficiency, and competitiveness by enabling the organization to harness data responsibly and strategically.

• Data Management

• Collect, clean, and preprocess data to ensure quality, integrity, and consistency.

• Build and maintain automated data pipelines for continuous data availability.

• Analytics & Modeling

• Design, develop, and test machine learning models and statistical analyses to address business problems.

• Evaluate, validate, and optimize model performance for accuracy, reliability, and scalability.

• Collaboration & Stakeholder Engagement

• Partner with IT, business units, and product owners to translate business requirements into data-driven solutions.

• Communicate insights, trends, and recommendations through compelling visualizations, reports, and presentations.

• Innovation & Knowledge Sharing

• Stay updated on emerging technologies, data science trends, and AI advancements.

• Support the development of organizational data science standards, documentation, and practices.
• Contribute to building a culture of data literacy and responsible data use across the organization.

• Governance & Compliance

• Ensure adherence to data privacy, security, and governance frameworks.

• Support risk management by applying best practices in data handling and compliance.

• Technical Expertise

• Proficiency in programming: Python, R, SQL

• Advanced proficiency in Python and SQL, intermediate proficiency in R
• Knowledge in machine learning (e.g., TensorFlow) and statistical analysis
• Hands-on experience with machine learning frameworks such as TensorFlow, PyTorch, or scikit-learn
• Experience with data visualization tools: Power BI, Tableau, Looker
• Familiarity with cloud platforms (Azure, AWS) and big data technologies (Hadoop, Spark)
• Strong foundation in data governance and data privacy standards

• Soft Skills

• Excellent communication and stakeholder management skills

• Analytical mindset with strong problem-solving abilities
• Strong organizational and time management skills
• Ability to explain complex technical concepts to non-technical audiences

• Education/Background

• Bachelor's or Master's degree in Computer Science, Statistics, Mathematics, Data Science, or related field

• Experience in applied data science roles within business or financial services preferred
• Experience in financial services, banking, or microfinance sector highly preferred but not essential
• Minimum 3-5 years of experience in applied data science or analytics roles
• Must be legally authorised to work in the Philippines without sponsorship

Technical

• Data wrangling and data quality assurance
• Advanced statistical methods (hypothesis testing, regression, time series, A/B testing)
• Model development, deployment, and evaluation
• Dashboard design and storytelling with data
• Cloud computing (Azure, AWS exposure)
• Automation and workflow scripting
• Version control and collaboration (e.g., Git)

Human Relations

• Strong leadership and mentoring skills
• Effective communicator and collaborator across teams
• Ability to manage stakeholder expectations

Personal Attributes

• God-centered and values-driven
• Confident, adaptable, and resilient
• Passionate about data and innovation
• Mature and grounded in decision-making

About the Role

The Data Scientist is responsible for collecting, analyzing, and interpreting large and complex datasets to help the organization make data-driven decisions. This role will design predictive models, develop algorithms, and provide actionable insights that support strategic and operational goals.

KEY RESPONSIBILITIES

• Collect, clean, and preprocess structured and unstructured data from multiple sources.
• Develop and implement statistical models, machine learning algorithms, and predictive analytics solutions.
• Interpret data, analyze results, and generate insights that influence decision-making.
• Create data visualizations, dashboards, and reports to effectively communicate findings to technical and non-technical stakeholders.
• Collaborate with cross-functional teams (engineering, product, business) to translate business problems into data solutions.
• Ensure data accuracy, integrity, and security while working with sensitive information.
• Stay updated with industry trends, tools, and best practices in data science, machine learning, and AI.

Key Qualifications & Skills:

• Bachelor's degree in Data Science, Computer Science, Statistics, Mathematics, or related field (Master's preferred).
• Proven experience as a Data Scientist or in a similar role.
• Strong proficiency in statistical tools and programming languages (Python, R, SQL).
• Hands-on experience with machine learning frameworks (TensorFlow, PyTorch, Scikit-learn).
• Experience with data visualization tools (Tableau, Power BI, matplotlib, seaborn).
• Familiarity with cloud platforms (AWS, GCP, Azure) is an advantage.
• Excellent analytical, problem-solving, and communication skills.

Work experience required:

• Have 3-5+ years working as a team member in delivery projects or initiatives leveraging Agile delivery practices, ideally with Product company experience
• Have experience of working within a complex, matrixed/helix model organization Formal Scrum Master experience would be a bonus
• An Agile certification would be a bonus

MS Office applications proficiency required / desired: 10/10

How to Apply

We would love to hear from you Don't miss out on this opportunity and apply now by completing your profile in detail through the link below.

About the role

Nidec Motor Philippines Corporation is seeking an exceptional Data Scientist to join our team in Metro Manila. This role focuses on transforming raw data into actionable insights using strong programming skills in R, Python, and SQL, alongside advanced statistical and machine learning techniques, including LLMs. Role will be responsible for data wrangling, developing predictive models, and visualizing complex findings with tools like Power BI or Tableau. Excellent communication is key to effectively convey these data-driven solutions to both technical and non-technical stakeholders.

What you'll be doing

• Programming Skills – knowledge of statistical programming languages like R, Python, and database query languages like SQL, Hive, Pig is desirable. Familiarity with Scala, Java, or C++ is an added advantage.
• Statistics – Good applied statistical skills, including knowledge of statistical tests, distributions, regression, maximum likelihood estimators, etc. Proficiency in statistics is essential for data-driven companies.
• Machine Learning – good knowledge of machine learning methods like k-Nearest Neighbors, Naive Bayes, SVM, Decision Forests and LLM tools such as GPT 4.o, Gemini, Claude.
• Strong Math Skills (Multivariable Calculus and Linear Algebra) - understanding the fundamentals of Multivariable Calculus and Linear Algebra is important as they form the basis of a lot of predictive performance or algorithm optimization techniques.
• Data Wrangling – proficiency in handling imperfections in data is an important aspect of a data scientist job description.

What we're looking for

1. Bachelor's Degree in Information Technology, Computer Science, Computer Engineering or any related degree.
2. 3+ years working as data scientist
3. 5+ years of experience in statistical programming
4. 5+ years of experience in database query languages
5. Knowledge in current trends in AI (Artificial Intelligence) and ML (Machine Learning)
6. Good communication skills
7. Amenable to work night shifts or on shifting schedules.

What we offer

At Nidec Motor Philippines Corporation, we are committed to providing our employees with a collaborative and supportive work environment that fosters professional growth and personal development. Some of the key benefits we offer include:

• Competitive Wages and Benefits – We provide employees with market-competitive pay and benefits package
• Meal, Transportation, Rice, Clothing Allowance
• Paid Leaves – We provide leave benefits to allow employees to take time off work – 20 Vacation, 20 Sick (convertible to cash if unused)
• Guaranteed Midyear Pay and 13th month pay
• HMO for employees and qualified dependents
• Productivity and Perfect Attendance Incentive; Performance-based Merit Increase
• Hybrid Work Setup: 2 days onsite work, 3 days work from home
• Business Travel – We provide opportunities to employees in qualified roles to visit other Nidec global sites
• Life / Personal Accident Insurance
• Study Assistance

About us

Nidec Motor Philippines Corporation (NMPC) is the leading provider of value-based solutions to all business platforms of its parent company, Nidec Corporation, a manufacturer of large and small precision motors based in Kyoto, Japan. As a shared service resource for the Nidec group of companies, Nidec Motor Philippines Corporation (NMPC) provides value-based solutions to all business platforms of Nidec and its service portfolio includes Administrative Services, Financial Services, Sales and Marketing Services, IT Services, Supply Chain Management Services, Technical Engineering Services and Procurement Services.

Through our benefits, development opportunities, and an inclusive work environment, we aim to create an organization our people are proud to represent.

The Data Scientist will collaborate with various teams to deliver data-driven insights and scalable solutions that align with business objectives, while identifying opportunities for data solutions and building business cases to demonstrate their value and ROI. Additionally, research and develop ML and GenAI solutions to enhance automation, evaluate emerging technologies to improve workflows, and support change management during transitions.

Position Responsibilities:

• Collaborate with multiple teams to provide data-driven insights, develop scalable data solutions, and support business objectives

• Identify opportunities for data driven solutions, assess feasibility, and build business cases to demonstrate value and ROI

• Research, prototype, and develop ML and GenAI powered solutions to enhance automation and decision-making processes

• Evaluate and introduce emerging technologies, best practices, and tools to improve the team's capabilities and workflows

• Provide support and facilitate change management during periods of transition.

Required Qualifications:

• D egree in Statistics, Math, Computer Science, Engineering , or other courses with equivalent technical experience

• Minimum of 5 years of applicable experience with a dvanced knowledge of programming languages and concepts (R , Python, Pyspark )

• Experience developing frontends and APIs are a plus ( Javascript , C, etc.)

• Experience in designing and developing AI, NLP, and LLM powered solutions

• Experience working and developing solutions on the cloud (Azure, AWS, GCP) is a plus

• Strong knowledge of machine learning and AI algorithms

• Strong communication skills; Able to simplify complex concepts to a broad audience

• Proficient in querying and analyzing both structured and unstructured data (SQL, NoSQL, JSON, MongoDB)

• Ability to manage multiple concurrent projects

• Knowledge in statistical tests, distributions, maximum likelihood estimators, statistical modelling techniques

• Knowledge in data visualization tools such as PowerBI , plotly , R Shiny, etc.

When you join our team:

• We'll empower you to learn and grow the career you want.
• We'll recognize and support you in a flexible environment where well-being and inclusion are more than just words.
• As part of our global team, we'll support you in shaping the future you want to see.

About Manulife and John Hancock

Manulife Financial Corporation is a leading international financial services provider, helping people make their decisions easier and lives better. To learn more about us, visit .

Manulife is an Equal Opportunity Employer

At Manulife/John Hancock, we embrace our diversity. We strive to attract, develop and retain a workforce that is as diverse as the customers we serve and to foster an inclusive work environment that embraces the strength of cultures and individuals. We are committed to fair recruitment, retention, advancement and compensation, and we administer all of our practices and programs without discrimination on the basis of race, ancestry, place of origin, colour, ethnic origin, citizenship, religion or religious beliefs, creed, sex (including pregnancy and pregnancy-related conditions), sexual orientation, genetic characteristics, veteran status, gender identity, gender expression, age, marital status, family status, disability, or any other ground protected by applicable law.

It is our priority to remove barriers to provide equal access to employment. A Human Resources representative will work with applicants who request a reasonable accommodation during the application process. All information shared during the accommodation request process will be stored and used in a manner that is consistent with applicable laws and Manulife/John Hancock policies. To request a reasonable accommodation in the application process, contact .

Working Arrangement

Hybrid

Axos Business Center, Corp

About This Job

As a Data Scientist, you will collaborate with cross-functional business units to identify Data Product solutions and monetization opportunities through the adoption of Artificial Intelligence, Data Science, Machine Learning, and Deep Learning, ensuring innovations drive measurable revenue growth and cost optimization.

Responsibilities

• Work closely with Axos Bank business units across Consumer Banking, Commercial Banking, Securities and Clearing, Marketing, Risk management, Fraud Management and Technology COE to develop and enhance models, detection systems, and other related analytics.

• Explore existing and new data sources as part of the data strategy frame to analytically prove or disprove the value of 3rd party data sources and identify innovative ways of activating revenue.

• Lead the end-to-end model development and production grade deployment lifecycle, including problem definition, data acquisition and preparation, feature engineering, model selection, training, validation, fine tuning, reinforcement learning and performance optimization; oversee deployment to production environments, continuous monitoring, and model retraining; collaborate with business stakeholders to ensure models are aligned to strategic goals and deliver measurable monetization, operational efficiency, and customer value.

• Design, fine-tune, and deploy Large Language Models (LLMs) and autonomous AI Agents to perform complex, multi-step tasks; integrate them with external data sources and APIs; and implement reinforcement learning, prompt engineering, and monetization strategies to drive measurable business impact.

• Collaborate with data governance and data quality to ensure data products are governed and monitored for quality.

• Implement data visualization tools and dashboards to facilitate effective communication of complex analytical results.

• Collaborate with cross-functional teams to understand business requirements and translate them into data-driven solutions.

• Communicate complex analytical findings and insights in a clear and concise manner to non-technical stakeholders.

Requirements

• Master's or Ph.D. in computer science or analytics program with 3-5 years of professional experience in data science or bachelor's in computer science or analytics program with 5-10 years professional experience in data science

• Statistical Theory and Application Proficiency

• Proficiency in descriptive and inferential statistics with hypothesis testing design experience. Identify dispersion, and distributions (mean, median, mode, variance, standard deviation, skewness, kurtosis).
• Apply probability theory and sampling techniques to draw valid conclusions from sample data. Estimate population parameters, calculate confidence intervals, and determine margins of error. Formulate null and alternative hypotheses aligned with business questions. Design and execute statistical tests (t-tests, ANOVA, chi-square, non-parametric tests, etc.) to validate assumptions. Determine sample sizes and statistical power to ensure robust test results. Interpret p-values, effect sizes, and statistical significance for decision-making.

• Experimental Design & A/B Testing, collaborate with product, marketing, and operations teams to design controlled experiments and quasi-experiments. Implement randomization, control groups, and blocking to reduce bias and confounding effects. Monitor experiments for compliance, data quality, and interim results.

• Machine Learning Expertise

• Expert knowledge of supervised and unsupervised machine learning techniques, including linear and logistic regression, neural networks, decision trees, random forests, gradient boosted machines, Bayesian methods, and clustering methodologies. Skilled at applying these algorithms to structured and unstructured data for classification, prediction, and segmentation.
• Experienced in leveraging and fine-tuning Large Language Models (LLMs) for natural language processing tasks such as text classification, sentiment analysis, entity extraction, summarization, and complex language understanding, enabling the development of AI solutions that combine statistical modeling with advanced NLP.
• Develop and deploy hybrid AI solutions that integrate traditional machine learning models with LLMs, orchestrating pipelines that utilize both structured data algorithms and state-of-the-art natural language capabilities. Responsible for continuous model evaluation, fine-tuning, and ensuring alignment with strategic business goals to drive automation, personalization, and enhanced decision-making.

• Collaborate cross-functionally to identify use cases, design model architectures, and implement scalable machine learning workflows that maximize business impact through actionable insights and monetization strategies.

• Familiarity with Cloud environments (GCP, AWS, Azure, Databricks, Snowflake)

• Develop and maintain scalable Python-based data science architectures to support the full machine learning lifecycle, including data ingestion, exploratory analysis, feature engineering, model development, validation, and deployment; utilize libraries such as pandas, NumPy, scikit-learn, Apache PySpark, TensorFlow, PyTorch, Kera's, LLM, Lang Chain, LangGraph to create efficient, reproducible, and production-ready analytics solutions

About Axos

Born digital-first, Axos delivers financial tools and services that allow individuals, small businesses, and companies to access and manage their money how, when, and where they want. We're a diverse team of dynamic, insightful, and independent innovators who are excited to provide technology-driven solutions that offer unbeatable value to our customers.

Axos Financial is our holding company and is publicly traded on the New York Stock Exchange under the symbol "AX" (NYSE: AX).

Learn More about working at Axos Business Center

Pre-Employment Background Check, Medical, and Drug Test:

All offers are contingent upon the candidate successfully passing a credit check, criminal background check, and pre-employment medical and drug screening.

Equal Employment Opportunity:

Axos is an Equal Opportunity employer. We are committed to providing equal employment opportunities to all employees and applicants without regard to race, religious creed, color, sex (including pregnancy, breast feeding and related medical conditions), gender, gender identity, gender expression, sexual orientation, national origin, ancestry, citizenship status, military and veteran status, marital status, age, protected medical condition, genetic information, physical disability, mental disability, or any other protected status in accordance with all applicable federal, state, and local laws.

Job Functions and Work Environment:

While performing the duties of this position, the employee is required to sit for extended periods of time. Manual dexterity and coordination are required while operating standard office equipment such as computer keyboard and mouse, calculator, telephone, copiers, etc.

The work environment characteristics described here are representative of those an employee may encounter while performing the essential functions of this position. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions of this position.

JOB DESCRIPTION

• Partner with stakeholders in defining business problems, identifying challenges, discovering opportunities, developing and implementing recommendations from data driven solutions and insights.
• Prioritize, scope and manage data science project and the corresponding key performance indicators (KPIs) for success
• Understand new and existing data sources and process pipelines and catalog/documenting them.
• Apply statistical analysis and visualization methods and generate hypotheses about underlying mechanics of business processes.
• Develop and implement AI solutions leveraging big data (e.g., comprehensive internal and alternative data sources) and advanced analytic tools and techniques (e.g., R, Python, Power BI, Tensor flow, Keras, etc.) across the organization that will contribute to revenue, cost/loss reduction, risk treatment, and compliance.
• Apply various Machine Learning and advanced analytics techniques while integrating domain knowledge into the Machine Learning solution.
• Establish best practices around ML Operationalization or MLDLC
• Promote collaboration with other data science teams within the organization and encourage reuse of artifacts
• Present to stakeholders possible opportunities, recommended solutions and impact to the business, and implementation proposals.

QUALIFICATIONS

Soft Skills:

1.Communication

• Employs multiple strategies for gathering information from key stakeholders.
• Communicate to stakeholders in a manner they understand - translating technical terms for the understanding of stakeholders
• Articulation to their work group - to understand the process as part of group

2.Leadership

• Works closely with team members; Engages and contributes to suggestions on how to improve
• Managing own self - Level of accountability, ownership

3.Stakeholder Management

• Has the ability to engage stakeholders in order to understand their perspective. Can put their perspective clearly. Works to identify possible compromises.
• Appropriately communicate results

4.Analytical Ability

• Demonstrates the ability to assess the available information, make a decision and act on it.

5.Others

• Proactive, with initiative and Project Management skills

Technical Skills:

1. Must have Data Modelling Experience
2. Basic Knowledge on Coding Skills, Data Management, Distributed Computing, Machine and Deep Learning, Storytelling and Visualization, Math and Statistics, AI Technical Skills
3. Application Experience: 2+ years of experience

4. Business and Industry Knowledge:

5. Basic knowledge of the industry

6. Has an understanding of the key products, services and markets of the organization.