เงื่อนไขการค้นหา

ทักษะ:

Compliance, Research, Python

ประเภทงาน:

งานประจำ

• Build and Optimize Modern AI Applications: Design and deploy a range of LLM-powered solutions, including Retrieval-Augmented Generation (RAG) pipelines, natural-language data querying, tool-using and function-calling workflows, and other Generative AI applications, to deliver accurate, grounded, and citable responses..
• Develop Statistical and Machine Learning Models: Develop, deploy, and maintain traditional statistical models and machine learning algorithms (e.g., regression, classification, clustering) to solve structured data problems and complement broader AI ini ...
• Collaborate with the Data Team: Work together on data preprocessing, embedding generation, and pipeline integration, leveraging the AWS enterprise data platform to supply clean, well-governed data for AI workloads..
• Optimize and Harden Production Services: Improve production AI services for reliability, scalability, latency, and cost, document solutions clearly, and communicate outcomes to both technical and non-technical stakeholders..
• Monitor and Observe Production AI: Implement tracing, observability, and dashboards to track quality, latency, drift, and cost-per-task across the model lifecycle..
• Ensure AI Ethical Standards, Compliance, and Data Privacy: Apply input/output guardrails, PII redaction, access controls, and grounding safeguards, in alignment with internal data governance policies and emerging AI regulations..
• Mitigate AI-Assisted Development Risks: Critically evaluate and audit AI-generated code to prevent security vulnerabilities, logic flaws, and technical debt, ensuring deep technical understanding rather than over-reliance on automated code generation..
• Monitor and Observe Production AI: Implement tracing, observability, and dashboards to track quality, latency, drift, and cost-per-task across the model lifecycle..
• Ensure AI Ethical Standards, Compliance, and Data Privacy: Apply input/output guardrails, PII redaction, access controls, and grounding safeguards, in alignment with internal data governance policies and emerging AI regulations..
• Mitigate AI-Assisted Development Risks: Critically evaluate and audit AI-generated code to prevent security vulnerabilities, logic flaws, and technical debt, ensuring deep technical understanding rather than over-reliance on automated code generation..
• Bachelor s Degree or higher in Computer Science, Artificial Intelligence, Data Science, Computer Engineering, or related technical field.
• 1 to 4 years of hands-on experience in AI/ML development, or an equivalent record of strong personal projects, research, or internships building applied AI/LLM solutions.
• Programming: Strong proficiency in Python for building AI/ML applications, including working with LLM APIs/SDKs and common AI libraries, as well as practical experience in data manipulation (e.g., using Pandas or SQL to clean and prepare data)..
• LLM Development: Hands-on experience building LLM-powered applications, including prompt design, tool/function calling, and connecting models to external data and tools..
• Retrieval & Vector Databases: Familiarity with vector databases, embedding models, and chunking/retrieval strategies (such as semantic chunking, hybrid search, and reranking)..
• Statistical Modeling & Machine Learning: Solid foundation in applied statistics, probability, and classical machine learning techniques. Proven ability to evaluate trade-offs and select the optimal modeling approach for specific business objectives..
• Cloud Computing: Experience with cloud platforms. AWS is the primary ecosystem for deploying and serving AI workloads, while familiarity with GCP or Azure is a welcome advantage..
• Engineering & LLMOps: Familiarity with version control (Git) and an awareness of general MLOps/LLMOps concepts (such as basic model testing, tracking performance, or managing prompts)..

ทักษะ:

ETL

ประเภทงาน:

งานประจำ

• Design and deliver cloud-native banking solutions on AWS.
• Build rapid prototypes and live demos for client engagements.
• Integrate AI and data capabilities into core banking platforms.
• The ideal candidate combines strong engineering depth, banking domain expertise, and the ability to translate ideas into working solutions quickly.
• Core Banking Transformation.
• Lending / loan origination and servicing.
• Credit decisioning systems.
• Payments, deposits, and investment platforms.
• Legacy cloud-native (rehost, replatform, refactor).
• Monolith microservices / event-driven architecture.
• Translate business requirements into scalable, secure, production-ready architectures.
• Client-Facing Demo & Prototyping (Critical Requirement).
• Build end-to-end functional prototypes and demos on AWS to showcase solutions.
• Working applications.
• API-driven services.
• AI/data-driven proof-of-value solutions.
• Solution workshops.
• Pre-sales discussions.
• Live demo sessions with business and technology stakeholders.
• Expected capability: Build a working demo (e.g., AI-powered credit workflow or customer 360 solution) within short timelines.
• AWS Cloud Engineering (Hands-on Senior Level).
• Architecture & Design.
• Microservices and event-driven patterns.
• API-first integration models.
• High availability, scalability, and resiliency.
• Security and regulatory compliance.
• Core AWS Stack.
• Compute: Lambda, ECS/EKS, EC2.
• Data: S3, Aurora/RDS, DynamoDB.
• Integration: API Gateway, Step Functions, EventBridge.
• Observability: CloudWatch and monitoring frameworks.
• DevOps & Automation.
• Infrastructure-as-Code (Terraform / CloudFormation / CDK).
• CI/CD pipelines and automated deployment.
• Ability to stand up environments quickly for demos and delivery.
• AI & Data Capabilities in Banking (Strong Preference).
• Data Engineering.
• Data lakes (S3-based architectures).
• ETL / ELT pipelines.
• Customer, transaction, credit, and risk datasets.
• Machine Learning & Analytics.
• Credit scoring and underwriting.
• Fraud detection / AML.
• Customer segmentation and personalization.
• GenAI & Modern AI.
• RAG-based solutions (e.g., document processing, KYC).
• AI assistants for banking users.
• AWS Bedrock / SageMaker / equivalent.
• LLM orchestration and vector search.
• Real-Time Decisioning.
• Real-time credit approvals.
• Fraud detection and alerts.
• Client Engagement & Thought Leadership.
• Act as a trusted technical advisor to financial services clients.
• Architecture discussions.
• Solution design workshops.
• Pre-sales and technical solutioning.
• Core banking modernization.
• Cloud + AI transformation.
• Bridge business, data, and technology stakeholders effectively.
• Banking technology / financial services IT.
• Core banking systems (lending, payments, deposits, investments).
• Core banking modernization or migration programs.
• Large-scale transformation initiatives.
• Cloud-native architecture and development.
• Microservices / distributed systems.
• Strong hands-on programming experience in Python (preferred), with the ability to build cloud-native applications, data pipelines, and rapid client-facing prototypes.
• Build working demos / PoCs under time pressure.
• Operate effectively in client-facing roles..
• Preferred Qualifications.
• Temenos, Mambu, Finacle, FLEXCUBE, nCino.
• Data engineering and analytics platforms.
• ML / GenAI use cases integrated into business workflows.
• Event-driven architecture.
• API-first ecosystems.
• Domain-driven design (DDD).
• AWS Certifications (Associate / Professional).
• Profile We Are Targeting.
• Hands-on builder (not a pure architect or program manager).
• Able to design, build, and demo solutions live to clients.
• Strong banking domain credibility.
• Bridges cloud + core banking + AI/data.
• Comfortable in pre-sales + delivery hybrid environments..

ทักษะ:

Statistics, Big Data, Python

ประเภทงาน:

งานประจำ

• Formulates advance data analytic, predictive analytic to proactively solve problems and/or create solutions for future business needs (Krungsri Auto App).
• Data Cleansing and Processing-massage and organize data for further advance analytic.
• Correlate disparate datasets.
• Develop new analytical methods and machine learning models (Personalized offering, Event trigger on App).
• Identify new business questions that can add value to organization.
• Conduct causality experiments by applying A/B experiments or any sciences-based approach to identify what best for determined business objectives.
• Discover and create new data features leading to data solutions creation.
• Using data visualization technique and presenting clear outcome as storytelling.
• Apply now if you have these advantages.
• Bachelor degree in Computer Science, Mathematics Science, Statistics Science, Computer Engineering or whoever having confident and ability enough to called self as Data Scientist.
• Must have experience in personalize recommendation and offering for mobile application users.
• 5+ years of experience in Telecom, Banking, Financing and Insurance preferred having 2 industries from the lists.
• 2+ years of experience in Big Data or AI/ML projects.
• 2+ years of experience in Enterprise Data Warehouse and/or data mining.
• Experience in solving business questions projects.
• Strong in Mathematics & Statistics.
• Strong in programming skill: prefer R, Python, SQL.
• Why join Krungsri?.
• As a part of MUFG (Mitsubishi UFJ Financial Group), we a truly a global bank with networks all over the world.
• We offer a striking work-life balance culture with hybrid work policies (3 days in office per week).
• Unbelievable benefits such as attractive bonuses, employee loan with special rates and many more.
• Apply now before this role is close. **.
• FB: Krungsri Career(http://bit.ly/FacebookKrungsriCareer [link removed]).
• LINE: Krungsri Career (http://bit.ly/LineKrungsriCareer [link removed]).
• Talent Acquisition Department
• Bank of Ayudhya Public Company Limited
• 1222 Rama III Rd., Bangpongpang, Yannawa, Bangkok 10120
• สอบถามข้อมูลเพิ่มเติม: Talent Acquisition Center 0-2-----000.
• หมายเหตุ ธนาคารมีความจำเป็นและจะมีขั้นตอนการตรวจสอบข้อมูลส่วนบุคคลเกี่ยวกับประวัติอาชญากรรมของผู้สมัคร ก่อนที่ผู้สมัครจะได้รับการพิจารณาเข้าร่วมงานกับธนาคารกรุงศรีฯ.
• Remark: The bank needs to and will have a process for verifying personal information related to the criminal history of applicants before they are considered for employment with the bank.
• Applicants can read the Personal Data Protection Announcement of the Bank's Human Resources Function by typing the link from the image that stated below.
• EN (https://krungsri.com/b/privacynoticeen).
• ผู้สมัครสามารถอ่านประกาศการคุ้มครองข้อมูลส่วนบุคคลส่วนงานทรัพยากรบุคคลของธนาคารได้โดยการพิมพ์ลิงค์จากรูปภาพที่ปรากฎด้านล่าง.
• ภาษาไทย (https://krungsri.com/b/privacynoticeth).

ทักษะ:

ETL, Big Data

ประเภทงาน:

งานประจำ

• Pipeline Development: Support the design and maintenance of scalable ETL/ELT pipelines for structured and unstructured datasets..
• AI Data Readiness: Assist in building data ingestion flows for Vector Databases and supporting RAG (Retrieval-Augmented Generation) architectures..
• Data Modeling: Contribute to the creation of robust data models and Feature Stores that serve both traditional analytics and machine learning workloads..
• Data Quality & Operations.
• Validation & Cleaning: Implement automated scripts to ensure high data integrity, reliability, and performance across the platform..
• Cloud Optimization: Assist in monitoring cloud resource usage (GCP/AWS) to ensure cost-efficiency and low-latency data access..
• Engineering Collaboration: Work closely with senior engineers to document data lineage and ensure the architecture is built for long-term scalability..
• Experience: Entry-level to 2 years of experience in data engineering, backend development, or a related technical internship.
• Portfolio: Demonstration of coding ability through a Github repository or a portfolio of data projects (e.g., building a personal API, a data scraper, or a small-scale ETL project)..
• Education: Bachelor s degree in Computer Engineering, Computer Science, Statistics, or a related technical field..
• Python: Solid foundation in writing clean, modular Python code.
• SQL: Proficiency in writing and optimizing complex queries for data analysis.
• Cloud Knowledge: Familiarity with at least one major cloud provider (GCP or AWS) and basic understanding of services like BigQuery, Redshift, or S3.
• AI Awareness: Interest in how data engineering supports AI; basic knowledge of unstructured data or vector search is a plus..
• What We Offer.
• Hands-on Multi-Cloud Experience: Get direct exposure to large-scale data environments on GCP/AWS and modern orchestration tools..
• Innovative Tech Stack: Work with cutting-edge tools at the intersection of Big Data and AI, including Vector DBs and automated data quality frameworks..
• Growth & Mentorship: A supportive environment where you will learn from senior engineers and have a clear path for professional development..
• Impactful Work: See your data pipelines directly power real-time marketing decisions and AI-driven products..
• If you re ready to build the data foundation for the next generation of AI, apply now!.

ทักษะ:

Data Analysis, Research, Market Research, English

ประเภทงาน:

งานประจำ

• Education: Fresh graduates in Computer Science. Do not apply if your most technically challenging work was an LLM-generated React website; please apply if you did machine learning, data analysis, or anything that required you to actually think and research..
• Business Understanding: The ability to understand business contexts and how your work impacts the company's bottom line is essential..
• Technical Core: Strong fundamentals in software engineering, algorithms and programm ...
• Soft Skills: Strong communication skills (English) and a drive to get things done..
• Mindset: We are looking for highly ambitious individuals who want to learn quickly, take ownership early, and grow faster than they would in a traditional graduate role..
• Conduct proofs-of-concept across new technologies, tools, and approaches the CTO is evaluating.
• Lead vendor and market research: identify options, assess fit, synthesize findings into clear recommendations.
• Write code and queries. Production-quality.
• Build and maintain data pipelines and data engineering work as needed.
• Perform data analysis to support product, operations, and strategic decisions.
• Own and track assigned cross-functional initiatives end to end, coordinating across teams.
• Support hiring, internal coordination, and day-to-day needs of the technical team.
• Company Description.
• PropertyScout is a Thailand-based Proptech startup providing a seamless end-to-end real estate transaction platform. Connecting over 5,500 agents and agencies with buyers, renters, and property owners, we serve thousands of satisfied customers monthly. Leveraging a rich database of most properties in Thailand and advanced technology, we digitize and automate 90% of real estate transactions, enabling agents to deliver exceptional service efficiently. With its focus on transparency and trust, PropertyScout has become a preferred platform for real estate in Thailand, as evidenced by hundreds of five-star reviews..
• Send your application now!.
• Please email your updated English CV to [email protected] using the format below.
• Email Subject: Technical Associate to the CTO - [Your Name].
• Please introduce yourself and answer the following questions in English.
• Why are you interested in this role?.
• When are you available to start?.
• What is your expected salary range?.
• What relevant experience do you have from internships, university projects, or coursework?.
• What is your proficiency level in spoken and written English?.

ทักษะ:

Product Development, Tableau, SQL

ประเภทงาน:

งานประจำ

• Identify valuable data sources and automate collection processes.
• Undertake preprocessing of structured and unstructured data.
• Analyze large amounts of information to discover trends and patterns.
• Build predictive models and machine-learning algorithms.
• Combine models through ensemble modeling.
• Present information using data visualization techniques.
• Propose solutions and strategies to business challenges.
• Collaborate with engineering and product development teams.
• BSc/BA in Computer Science, Engineering or relevant field; graduate degree in Data Science or other quantitative field is preferred.
• Proven experience as a Data Scientist or Data Analyst.
• Experience in data mining.
• Experience using business intelligence tools (e.g. Tableau).
• Knowledge of SQL and Python.
• Understanding of machine-learning and operations research.
• Analytical mind and business acumen.
• Strong math skills (e.g. statistics).
• Problem-solving aptitude.
• Excellent communication and presentation skills Working knowledge of message queuing, stream processing, and highly scalable big data data stores.
• Applicants can read the Personal Data Protection Announcement of the Bank's Human Resources Function by typing the link from the image that stated below.
• EN: (https://krungsri.com/b/privacynoticeen).
• ผู้สมัครสามารถอ่านประกาศการคุ้มครองข้อมูลส่วนบุคคลส่วนงานทรัพยากรบุคคลของธนาคารได้โดยการพิมพ์ลิงค์จากรูปภาพที่ปรากฎด้านล่าง.
• ภาษาไทย: (https://krungsri.com/b/privacynoticeth).
• หมายเหตุ ธนาคารมีความจำเป็นและจะมีขั้นตอนการตรวจสอบข้อมูลส่วนบุคคลเกี่ยวกับประวัติอาชญากรรมของผู้สมัคร ก่อนที่ผู้สมัครจะได้รับการพิจารณาเข้าร่วมงานกับธนาคารกรุงศรีฯ.
• Remark: The bank needs to and will have a process for verifying personal information related to the criminal history of applicants before they are considered for employment with the bank.