What Jobs are available for Data Intelligence in Thailand?

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

DUTIES AND RESPONSIBILITIES

• Collaborate cross-functionally with business, technical, and operational teams
  to ensure alignment of digital energy solutions with organizational goals and support end-to-end project execution from ideation to impact.
• 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.

JOB SPECIFICATION

• Ability to
  translate complex analytical results into strategic business insights,
  effectively bridging technical solutions with practical business applications in the energy sector.
• 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.

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

Company Description
At Western Digital, our vision is to power global innovation and push the boundaries of technology to make what you thought was once impossible, possible.

At our core, Western Digital is a company of problem solvers. People achieve extraordinary things given the right technology. For decades, we've been doing just that—our technology helped people put a man on the moon and capture the first-ever picture of a black hole.

We offer an expansive portfolio of technologies, HDDs, and platforms for business, creative professionals, and consumers alike under our Western Digital, WD, WD_BLACK, and SanDisk Professional brands.

We are a key partner to some of the largest and highest-growth organizations in the world. From enabling systems to make cities safer and more connected, to powering the data centers behind many of the world's biggest companies and hyperscale cloud providers, to meeting the massive and ever-growing data storage needs of the AI era, Western Digital is fueling a brighter, smarter future.

Today's exceptional challenges require your unique skills. Together, we can build the future of data storage.

Job Description
ESSENTIAL DUTIES AND RESPONSIBILITIES:

• Collaborate with cross-functional teams to develop high-impact data science solutions that improve productivity and operations metrics
• Analyze large-scale data and develop machine learning/AI models to drive business value and improve KPIs
• Design, prototype, and implement machine learning models and algorithms to solve specific Manufacturing problems
• Researching and developing scalable computer vision and machine learning solutions for complex problems
• Create and maintain web applications to support data science initiatives and facilitate data-driven decision making
• Interpret actionable insights from data and metadata sources, communicating findings to stakeholders for product improvement
• Prepare and deliver presentations with data visualizations and business conclusions

Qualifications
REQUIRED:

• Bachelor's degree in Computer Engineering, Software Engineering, Data Science, and Robotics & AI Engineering with relevant industry or academic experience in data analytics
• Proficiency in SQL, Big Data platforms, and cloud services (e.g., AWS)
• Strong background in applied statistics, statistical modeling, and practical experience with ML and AI algorithms.
• Required: Python, Tensorflow framework, Computer Vision
• Familiar with collaborative solutions, model & code versioning (Github), and solution packaging (Docker)
• Strong communication, analytical, and problem-solving skills.

Preferred

• Knowledge of AI/ML model development and lifecycle management.
• Experience with cloud-based solutions and collaborative tools (e.g., Github, Docker).
• Experience in Computer Vision and image processing techniques.
• Experience in web development.
• Familiarity with advanced machine learning techniques (e.g., neural networks, NLP, deep learning).
• Ability to communicate complex technical concepts to non-technical stakeholders.
• Proactive approach to learning and implementing emerging technologies.

Additional Information
Western Digital thrives on the power and potential of diversity. As a global company, we believe the most effective way to embrace the diversity of our customers and communities is to mirror it from within. We believe the fusion of various perspectives results in the best outcomes for our employees, our company, our customers, and the world around us. We are committed to an inclusive environment where every individual can thrive through a sense of belonging, respect and contribution.

Western Digital is committed to offering opportunities to applicants with disabilities and ensuring all candidates can successfully navigate our careers website and our hiring process. Please contact us at to advise us of your accommodation request. In your email, please include a description of the specific accommodation you are requesting as well as the job title and requisition number of the position for which you are applying.

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.