What Jobs are available for Analysts in Thailand?

Overview:

Data scientists are specialists who turn raw data into valuable insights and actionable decision. They use their analytical skills, programming skills, statistical expertise, and knowledge of machine learning to build advance analytics data product that help the company make better decisions, improve products, and understand customers.

Detailed Responsibilities:

 Analyze complex data sets using statistical methods and machine learning algorithms to uncover actionable patterns, trends, and insights that drive business outcomes.

Clean, preprocess, and transform raw data into usable formats for analysis and modeling.

uild predictive and optimization models to support strategic decision-making and improve operational efficiency.

esign and execute scientific experiments, including measurement and validation of analytical models.

evelop compelling data visualizations and dashboards to communicate findings effectively to stakeholders at all levels.

resent insights and recommendations clearly to both technical and non-technical audiences, ensuring alignment with business objectives.

ollaborate closely with cross-functional teams to translate data-driven insights into actionable business strategies.

reate comprehensive reports, presentations, and storytelling materials to document analyses and support organizational learning.

ducate and support stakeholders in understanding advanced analytics techniques and their applications within the manufacturing context.

aintain key artefacts such as sprint backlogs, experiment logs, data sets, notebooks, model artifacts, visualizations, and research documentation in alignment with Agile methodologies.

Skill Requirements

achelor's or Master's degree in Computer Science, Statistics, Mathematics, Data Science, Engineering, or a related field.

t least 5+ Yrs proven experience as a Data Scientist, Data Analyst, or in a similar analytical role, preferably within a manufacturing or industrial environment.

trong expertise in statistical analysis, data mining, and machine learning techniques.

roficiency in programming languages such as Python or R, and experience with data science libraries and frameworks.

ands-on experience with data cleaning, preprocessing, and feature engineering.

dvanced skills in data visualization tools (e.g., Tableau, Power BI, Matplotlib, Seaborn) to present complex findings effectively.

olid understanding of experiment design and scientific measurement methodologies.

xcellent communication skills, with the ability to explain complex concepts to diverse

xperience working in Agile environments and familiarity with Agile practices.

Other Requirements:

xperience with big data technologies (e.g., Hadoop, Spark) and cloud platforms (e.g., AWS, Azure, GCP) is advantageous.

elevant industry certifications in data science, machine learning, or analytics are a plus.

nowledge of manufacturing processes and operational excellence frameworks will be highly regarded.

emonstrated ability to work effectively in multicultural and geographically dispersed teams.

Work Set-up: Hybrid (1-day WFH)

Onsite Location: Soi Sukhapiban, Dokmai, Bangkok

Cathcart Technology is partnering with a global leader in advanced manufacturing solutions to hire a Data Science Manager. This is a fantastic opportunity to build and lead a new Data Science team that will drive predictive quality, yield optimization, and defect reduction across large-scale production operations.

What you'll do

• Lead the development of advanced statistical models & predictive analytics to enhance manufacturing quality and efficiency.
• Apply DOE, RSM, SPC, and machine learning methods to prevent defects and optimize processes.
• Collaborate with engineering and operations teams to translate complex data science into real-world impact.
• Build, mentor, and manage a high-performing team of 4–5 data scientists and analysts.
• Define and execute the long-term data science strategy for manufacturing excellence.

What they're looking for

• 5+ years' experience in data analytics, statistical modelling, or applied data science.
• Proven leadership and team management experience.
• Advanced knowledge of multivariate analysis, Bayesian methods, hypothesis testing, and experimental design.
• Strong programming skills in Python/R and SQL, plus hands-on experience with ML frameworks (scikit-learn, TensorFlow, PyTorch).
• Proficiency with statistical tools such as JMP or Minitab.
• Excellent communication skills and ability to work with cross-functional teams.
• Good English (spoken and written).

Why apply to this opportunity

This role puts you at the centre of transforming how data science powers world-class manufacturing quality. You'll have the chance to:

• Build and shape a new data science team.
• Work directly with global engineering leaders.
• Deliver cutting-edge, impactful solutions at scale.

Please apply now or contact Dollada (Toon) at for a confidential discussion.

Responsibilities

• Identify valuable data sources and automate data collection processes
• Collect, clean, and validate structured and unstructured data from multiple internal and external systems
• Extract, transform, and engineer features from diverse data sources (ERP, IoT, finance, external datasets)
• Analyze large datasets to uncover trends, patterns, and actionable insights
• Design, build, and deploy predictive models, machine learning algorithms, and AI-driven solutions
• Improve performance through feature engineering, optimization, and ensemble modeling
• Monitor model accuracy, fairness, and drift; retrain and recalibrate as needed
• Present findings using effective data visualization techniques to support decision-making
• Propose data-driven solutions and strategies to address complex business challenges
• Collaborate closely with IT, engineering, and product development teams to integrate solutions into business operations

Qualifications

• Bachelor's or Master's degree in Data Science, Statistics, Applied Mathematics, Computer Science, or a related field
• Strong programming skills in Python, R, and SQL
• Knowledge of Machine Learning, Data Mining, and Data Visualization
• Experience with data visualization tools (Tableau, Power BI, matplotlib, seaborn)
• Experience in data mining
• Familiarity with cloud platforms (AWS, Azure, GCP)
• Problem-solving skills
• Strong communication and collaboration abilities

หน้าที่ความรับผิดชอบ (Key Responsibilities):

·    ออกแบบและดำเนินการวิเคราะห์ข้อมูลเชิงลึก เพื่อสนับสนุนกลยุทธ์องค์กรและเพิ่มประสิทธิภาพในเรื่องต่างๆ เช่น: การตรวจสอบและลดปัญหา Frauded, การวางแผนเพื่อ Optimization

·    สร้าง Dashboard และรายงานแบบ Interactive โดยใช้ Power BI

·    สร้างแบบจำลองทางสถิติ / Machine Learning สำหรับวิเคราะห์ เช่น Sales Forecast, Fuel Consumption T_rends, Customer Segmentation หรือ Anomaly Detection

·    แปลง Pain Point ทางธุรกิจให้เป็นโจทย์วิเคราะห์ข้อมูล และนำเสนอ Insight ที่ actionable และ measurable

·    ร่วมกำหนด KPI และวาง Data Strategy ร่วมกับทีมธุรกิจและน้องๆ ในทีม

·    ถ่ายทอดผลการวิเคราะห์ให้ทีมปฏิบัติการเข้าใจง่าย พร้อมแนวทางการแก้ปัญหาที่นำไปใช้ได้จริง

คุณสมบัติ (Qualifications):

·    ปริญญาโทขึ้นไปในสาขา Data Science, Statistics, Computer Science, Business Analytics หรือสาขาอื่นที่เกี่ยวข้อง

·    มีประสบการณ์อย่างน้อย 5-10 ปี โดยเฉพาะในบริบทธุรกิจจริง เช่น retail, logistics

·    เชี่ยวชาญการสร้าง Dashboard ด้วย Power BI, Tableau หรือเครื่องมือใกล้เคียง

·    มีทักษะเขียนโปรแกรมและวิเคราะห์ข้อมูลด้วย Python, R, SQL

·    มีความรู้เรื่อง Machine Learning และสามารถใช้ Libraries เช่น scikit-learn, XGBoost, PyTorch ได้

·    มีประสบการณ์ในการทำ Forecasting, Clustering และ Predictive Analytics

·    มีทักษะการคิดเชิงวิเคราะห์สูง สามารถเชื่อมโยงข้อมูลกับบริบทธุรกิจได้ดี

·    หากมีประสบการณ์กับ Cloud Platform เช่น AWS, GCP, Azure จะได้รับการพิจารณาเป็นพิเศษ

ออกแบบและดำเนินการวิเคราะห์ข้อมูลเชิงลึก เพื่อสนับสนุนกลยุทธ์องค์กรและเพิ่มประสิทธิภาพในเรื่องต่างๆ เช่น: การตรวจสอบและลดปัญหา Frauded, การวางแผนเพื่อ Optimization.

สร้าง Dashboard และรายงานแบบ Interactive โดยใช้ Power BI.

สร้างแบบจำลองทางสถิติ / Machine Learning สำหรับวิเคราะห์ เช่น Sales Forecast, Fuel Consumption T_rends, Customer Segmentation หรือ Anomaly Detection.

แปลง Pain Point ทางธุรกิจให้เป็นโจทย์วิเคราะห์ข้อมูล และนำเสนอ Insight ที่ actionable และ measurable.

ร่วมกำหนด KPI และวาง Data Strategy ร่วมกับทีมธุรกิจและน้องๆ ในทีม.

ถ่ายทอดผลการวิเคราะห์ให้ทีมปฏิบัติการเข้าใจง่าย พร้อมแนวทางการแก้ปัญหาที่นำไปใช้ได้จริง.

ปริญญาโทขึ้นไปในสาขา Data Science, Statistics, Computer Science, Business Analytics หรือสาขาอื่นที่เกี่ยวข้อง.

มีประสบการณ์อย่างน้อย 5-10 ปี โดยเฉพาะในบริบทธุรกิจจริง เช่น retail, logistics.

เชี่ยวชาญการสร้าง Dashboard ด้วย Power BI, Tableau หรือเครื่องมือใกล้เคียง.

มีทักษะเขียนโปรแกรมและวิเคราะห์ข้อมูลด้วย Python, R, SQL.

มีความรู้เรื่อง Machine Learning และสามารถใช้ Libraries เช่น scikit-learn, XGBoost, PyTorch ได้.

มีประสบการณ์ในการทำ Forecasting, Clustering และ Predictive Analytics.

มีทักษะการคิดเชิงวิเคราะห์สูง สามารถเชื่อมโยงข้อมูลกับบริบทธุรกิจได้ดี.

หากมีประสบการณ์กับ Cloud Platform เช่น AWS, GCP, Azure จะได้รับการพิจารณาเป็นพิเศษ.

Roles and Responsibilities

Data Analysis and Processing

• Collect, analyze, and process data from various sources to support business decision-making.
• Develop statistical models and machine learning algorithms to predict business trends and enhance operational efficiency.
• Ensure data accuracy and improve data quality for practical use.

AI and Machine Learning Model Development

• Design, build, and improve machine learning and deep learning models to address business challenges.
• Monitor and enhance model performance, including managing issues like overfitting, bias, and data drift.
• Apply data mining and natural language processing (NLP) techniques for data analysis.

Collaboration with Teams and Relevant Departments

• Work closely with data science teams, data engineers, data analysts, and business departments to deliver results aligned with organizational goals.
• Present analysis findings and strategic recommendations to executives.
• Translate and communicate technical information in an understandable manner for non-technical teams.

Data Management and Related Tools

• Design and maintain efficient data architectures for practical use.
• Use data analysis tools such as Python, R, SQL, TensorFlow, PyTorch, Scikit-learn, Power BI, or Tableau.
• Work with Big Data systems such as Hadoop, Spark, and relational databases (SQL, NoSQL).

Qualifications

• Bachelor's degree or higher in
  Data Science, Computer Engineering, Computer Science, Mathematics, Statistics, Artificial Intelligence (AI),
  or related fields.
• 2-5 years
  of experience in
  Data Science, Machine Learning,
  or
  AI
  .
• Proficiency in data analysis, machine learning, deep learning, natural language processing (NLP), and computer vision.
• Programming skills in
  Python, R, SQL, Scala
  , and familiarity with libraries like
  TensorFlow, PyTorch, Scikit-learn
  .
• Experience working with
  Big Data, Cloud Platforms (AWS, Google Cloud, Azure)
  , and
  data visualization tools
  like
  Power BI, Tableau
  .
• Strong problem-solving, analytical thinking, and ability to present data insights to executives.
• Ability to collaborate effectively with cross-functional teams.

Responsibility

• Develop customer and business insights to identify business opportunities or resolve business challenges, and provide actionable recommendations to guide business decisions
• Prepare data from different data sets for building analytical models and delivering customer insights and recommendations to guide business decisions.
• Communicate findings and build buy-in with key stakeholders through data visualizations
• Deliver pre and post campaign analysis to guide the design and optimization of analytical models and personalized marketing campaigns
• Design, develop, and deploy analytical models and advanced analytic solutions using statistical techniques and machine learning technologies.
• Work with engineers to implement end-to-end process from model development to testing, validation, deployment, and lifecycle support.
• Research and Development on novel data science and analytics tools and ML/AI technology

Background/ Experiences

• 3+ years of Experience working with customer-centric data at big data-scale and applying machine learning, optimization and statistical methods to large datasets in various industries: financial services, telecom, retails, insurance, e-commerce, or related industries.
• Strong statistical knowledge, superior analytical abilities, and good knowledge of business intelligence solutions
• Full stack experience in data collection, aggregation, analysis, visualization, productionisation, and monitoring of ML products - MLOps
• Experience in being able to translate business needs into executable data science and analytics solutions
• Proven track record in client engagement, relationship building, and project management is PLUS

Knowledge & Skills

• Bachelor's degree or equivalent experience in quantitative field (Statistics, Mathematics, Computer Science, Engineering)
• Deep understanding of mathematics and statistical modeling, predictive modeling, and machine-learning algorithms with hands-on experience with Machine Learning frameworks.
• Excellent Proficiency in programing languages (SQL, R, Python) and Experience with business intelligence solutions (Tableau, PowerBI or Advanced Excel)
• Hand-on experience in data engineering, working with big data technology (Spark/Hadoop) and cloud platforms such as Azure, AWS, or GCP
• Excellent verbal, written, and interpersonal communication skills (both Thai and English)

Location: Krungthep Kreetha (ONSITE)

Website:

Job Scope:

• Conduct in-depth energy data analysis to develop strategic recommendations that drive sales growth, enhance customer service, and optimize financial performance.
• Development and implementation of advanced Digital Energy Solutions, including Aggregator Platforms, Solar/Load Forecasting Systems, Energy Management System and Demand Response.
• Creation and execution of advanced analytics and model development, including the technical design, training, and deployment of sophisticated forecasting models leveraging machine learning (ML) and AI-based methodologies to deliver predictive accuracy and actionable insights.
• Serve as a subject-matter expert in integrating advanced analytics to enhance energy business and drive strategic decision-making.
• Build and foster a data-driven culture to enhance the efficiency, sustainability, and profitability of energy business.
• Stay updated with the latest advancements in data science and machine learning to continuously innovate and deliver impactful solutions.

Qualification:

• Bachelor's degree in Computer Engineering or any related fields.
• Advanced knowledge of machine learning algorithms and techniques, with practical experience in statistical analysis and predictive modeling.
• Proficiency in data manipulation and analysis tools such as Pandas, NumPy, dplyr, and the ability to work with both structured and unstructured data sets.
• Hands-on experience with machine learning frameworks (e.g., Scikit-learn, TensorFlow, Keras, PyTorch) for developing and deploying models.
• Expertise in data visualization tools (e.g., Matplotlib, Seaborn, ggplot2, BI) to effectively communicate insights.
• Familiarity with big data technologies (e.g., Hadoop, Spark) and cloud platforms (e.g., AWS, Google Cloud, Azure) is highly advantageous

Data Science for Decision Engine

We are seeking a Data Scientist specializing in credit decision engine development to drive data-driven lending decisions and risk assessment. The ideal candidate will combine strong analytical skills with deep understanding of credit process.

Key Responsibilities

Model Development & Deployment

• Develop and maintain credit risk assessment and lending decisions modules
• Expertise for handling large financial databases and credit data manipulation
• Design and implement credit-risk decisioning model solutions using API-based frameworks (e.g., Flask, FastAPI) or event-driven architecture (e.g., Kafka, Pub/Sub), along with other suitable technologies
• Monitor model performance to ensure high accuracy and reliability in credit decisions

Data Analysis & Risk Assessment

• Clean and preprocess financial datasets, particularly credit lending and risk data
• Conduct advanced statistical analyses to support risk assessment and lending decisions

Required Qualifications

Technical Skills

• Proficiency in Python, SQL, and machine learning libraries (TensorFlow, PyTorch, Scikit-Learn)
• Experience with cloud platforms (AWS,GCP) for model deployment
• Knowledge of statistical and machine learning techniques for risk modeling

Domain Expertise

• Understanding of credit lending and risk assessment principles
• Experience in financial data analysis within regulatory constraints
• Proven track record in developing credit decision engines (optional)

Education & Experience

• Bachelor's degree or higher in Statistics, Computer Science, Mathematics, or related field
• Minimum 3 years experience in retail lending or similar role

Additional Requirements

• Strong communication skills for presenting complex findings and process flow to management
• Experience with data visualization tools (Tableau, Power BI)
• Ability to work collaboratively with cross-functional teams

Contact : K.Panyatip

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