เงื่อนไขการค้นหา

ประสบการณ์:

3 ปีขึ้นไป

ทักษะ:

Data Analysis, SQL, Python, English, Thai

ประเภทงาน:

งานประจำ

• Research on AI/ML, MarTech and AdTech to explore new tools and techniques.
• Prototype and test hyper-personalization engine using these innovations to ensure benefits and efficiency before full-scale deployment.
• Design, implement and automate personalization engine and recommendation system to enhance customer experiences and boost sales and marketing.
• Leverage Advanced analytics, AI/ML, and data mining techniques across various use cases to address business challenges.
• Design and conduct experiments, evaluate and maintain model to improve performance.
• Engage with key stakeholders, including IT, business, campaign and data teams to align on business requirements and integrate data solutions into our platforms.
• Participate in the vendor selection processes to identify and ensure the best external partners for data science and AI/ML projects.
• Bachelor s Degree or higher in Computer Science, Data Science, Engineering, Statistics, or any related field.
• Minimum of 3-5 years experience in data field and at least 2 years in data science, AI/ML engineer or a related field.
• Proficiency in some of the following: Recommendation engine, Reinforcement Learning, Python, PySpark and SQL and etc.
• Experience in building tools / models to support retention, up-cross selling, optimization, mobile app data and digital marketing is a plus.
• Ability to communicate and collaborate with cross-functional teams.
• Growth mindset and openness to continuously learning and facing new projects and new technologies.
• ท่านสามารถอ่านและศึกษานโยบายความเป็นส่วนตัวของธนาคารกรุงไทย จำกัด (มหาชน) ที่ https://krungthai.com/th/content/privacy-policy ทั้งนี้ ธนาคารไม่มีเจตนาหรือความจำเป็นใดๆ ที่จะประมวลผลข้อมูลส่วนบุคคลที่มีความอ่อนไหว รวมถึงข้อมูลที่เกี่ยวข้องศาสนาและ/หรือหมู่โลหิต ซึ่งอาจปรากฏอยู่ในสำเนาบัตรประจำตัวประชาชนของท่านแต่อย่างใด ดังนั้น กรุณาอย่าอัปโหลดเอกสารใดๆ รวมถึงสำเนาบัตรประจำตัวประชาชน หรือกรอกข้อมูลส่วนบุคคลที่มีความอ่อนไหวหรือข้อมูลอื่นใด ซึ่งไม่เกี่ยวข้องหรือไม่จำเป็นสำหรับวัตถุประสงค์ในการสมัครงานไว้บนเว็บไซต์ นอกจากนี้ กรุณาดำเนินการให้แน่ใจว่าได้ดำเนินการลบข้อมูลส่วนบุคคลที่มีความอ่อนไหว (ถ้ามี) ออกจากเรซูเม่และเอกสารอื่นใดก่อนที่จะอัปโหลดเอกสารดังกล่าวไว้บนเว็บไซต์แล้วด้วย ทั้งนี้ ธนาคารมีความจำเป็นต้องเก็บรวบรวมข้อมูลส่วนบุคคลเกี่ยวกับประวัติอาชญากรรมของท่านเพื่อบรรลุวัตถุประสงค์ในการพิจารณารับบุคคลเข้าทำงาน หรือการตรวจสอบคุณสมบัติ ลักษณะต้องห้าม หรือพิจารณาความเหมาะสมของบุคคลที่จะให้ดำรงตำแหน่ง ซึ่งการให้ความยินยอมเพื่อเก็บรวบรวม ใช้ หรือเปิดเผยข้อมูลส่วนบุคคลเกี่ยวกับประวัติอาชญากรรมของท่านมีความจำเป็นสำหรับการเข้าทำสัญญาและการได้รับการพิจารณาตามวัตถุประสงค์ดังกล่าวข้างต้น ในกรณีที่ท่านไม่ให้ความยินยอมในการเก็บรวบรวม ใช้ หรือเปิดเผยข้อมูลส่วนบุคคลเกี่ยวกับประวัติอาชญากรรม หรือมีการถอนความยินยอมในภายหลัง ธนาคารอาจไม่สามารถดำเนินการเพื่อบรรลุวัตถุประสงค์ดังกล่าวข้างต้นได้ และอาจ ทำให้ท่านสูญเสียโอกาสในการได้รับการพิจารณารับเข้าทำงานกับธนาคาร .

ทักษะ:

ETL, Python

ประเภทงาน:

งานประจำ

• รวมข้อมูลดิบจากแหล่งข้อมูลต่างๆ ทั้งภายและภายนอก และสร้างอัลกอริทึมและสร้างต้นแบบ.
• การรวบรวมข้อมูลที่มีโครงสร้าง (Structured Data) และไม่มีโครงสร้าง (Unstructured Data) ประเมินความต้องการและวัตถุประสงค์ทางธุรกิจ.
• จัดระเบียบข้อมูลดิบ นำข้อมูลมาทำความสะอาด (Data Cleansing + Shaping + ETL) รวมถึงจัดเตรียมข้อมูลสำหรับการสร้างแบบจำลอง.
• ทำการ Explore Data ด้วย Data Visualization Tools.
• หาวิธีการปรับปรุงคุณภาพของข้อมูล และสร้างความน่าเชื่อถือของข้อมูลดูแนวโน้มและ Patterns.
• ใช้ AI/ML การทำนาย คาดการณ์ (Predictive) และรายงานผล.
• ปริญญาตรี สาขา วิทยาการคอมพิวเตอร์ วิศวกรรมศาสตร์ คณิตศาสตร์ สถิติ หรือสาขาอื่นที่เกี่ยวข้อง.
• มีประสบการณ์ในการทำ Data Visualization.
• มีประสบการณ์การใช้ Cloud Platform.
• มีประสบการณ์การใช้ Python เช่น Pandas, Numpy, Scikit-learn, Matplotlib and PyTorch.
• มีประสบการณ์ การใช้ Machine Learning เช่น regression, classification, clustering and association.
• มีความเข้าใจในสถิติข้อมูล.
• มีทักษะการนำเสนอ โดยสามารถนำความคิดที่ซับซ้อนมาทำให้เป็นรูปแบบที่เข้าใจง่าย.
• นักสื่อสารที่ดีพร้อมการจัดการผู้มีส่วนได้ส่วนเสียได้.
• มีทักษะการแก้ปัญหา.

ทักษะ:

Data Analysis, SQL, Excel, English

ประเภทงาน:

งานประจำ

• Data Analysis: Conduct in-depth analysis of retail and wholesale business data to address specific business questions and challenges.
• Insight Generation: Interpret results from dashboards and data analyses to develop actionable insights and strategic recommendations.
• Requirement Gathering: Identify business problems, gather requirements, and propose potential solutions, including leveraging AI to enhance business operations.
• ML Model creations: Create data analytic model including both deterministic and machine learning model.
• AI vendors coordination's: Collaborate with external AI suppliers to align project objectives with technological capabilities.
• Cross-Departmental Collaboration: Work with various departments to develop and implement data-driven strategies that optimize business processes and decision-making.
• Communication: Act as a liaison between stakeholders and AI vendors, ensuring clear communication understanding of project requirements.
• Data analytics and AI Strategy Design; Design and recommend how Business Intelligence (BI) and AI technologies can address business problems and provide further insights.
• Decision making support: Present key findings from own analysis and strategic recommendations to business counterparts and senior management, focusing on project approaches and strategic planning.
• Bachelors' Degree or higher in Computer Science, Engineering, Information Technology, Management Information System.
• Strong business acumen, with a deep understanding of retail and wholesale business.
• At least 5 years of proven experience as a data analytic role (Retail or E-Commerce Business is preferable).
• Hands-on Experience in SQL, data cloud platform (e.g. Databricks, Snowflake, GCP, or AWS) and high proficiency in excel.
• Good knowledge of Statistics.
• Experience in Python (Pandas, Numpy, SparkSQL), Data Visualization (Tableau, Power BI) is a plus.
• Excellent communication skills with a ability to convey complex findings to non-technical stakeholders.
• Fluent in Thai and English.
• Having good attitude toward team working & willing to work hard.

ทักษะ:

Python, Instrument, English

ประเภทงาน:

งานประจำ

• Implement python application to handle data structure/format to price financial instruments using both self-created libraries embedded and/or pre-defined library or Refinitiv quantitative pricing service API.
• Participate in requirement discussion both technical and non-technical aspect with relevant parties mainly located in Europe and India.
• Produce minimum level of requirement document.
• Provide 3rd level support of application.
• Required skills and experience New graduated are also welcome.
• Good knowledge in Python programming language and application design.
• Understand concept of API (application programming interface).
• Intermediate level in spoken and written English.
• Positive and open mindset, eager to learn new technologies.
• Preferred skills, interests (not required but with advantage) Strong interest in financial market, trading securities and investment.
• Knowledge in statistic and calculus (e.g. partial differential equation).
• Concept of financial market and financial instrument especially derivatives.
• LSEG is an equal opportunties employer, that seeks to offer an inclusive environment to all colleagues. Furthermore, LSEG has committed to reduce its carbon emissions by 50% by 2030, and to reach net zero by 2040 LSEG is a leading global financial markets infrastructure and data provider. Our purpose is driving financial stability, empowering economies and enabling customers to create sustainable growth. Our purpose is the foundation on which our culture is built. Our values of Integrity, Partnership, Excellence and Change underpin our purpose and set the standard for everything we do, every day. They go to the heart of who we are and guide our decision making and everyday actions. Working with us means that you will be part of a dynamic organisation of 25,000 people across 65 countries. However, we will value your individuality and enable you to bring your true self to work so you can help enrich our diverse workforce. You will be part of a collaborative and creative culture where we encourage new ideas and are committed to sustainability across our global business. You will experience the critical role we have in helping to re-engineer the financial ecosystem to support and drive sustainable economic growth. Together, we are aiming to achieve this growth by accelerating the just transition to net zero, enabling growth of the green economy and creating inclusive economic opportunity. LSEG offers a range of tailored benefits and support, including healthcare, retirement planning, paid volunteering days and wellbeing initiatives. We are proud to be an equal opportunities employer. This means that we do not discriminate on the basis of anyone s race, religion, colour, national origin, gender, sexual orientation, gender identity, gender expression, age, marital status, veteran status, pregnancy or disability, or any other basis protected under applicable law. Conforming with applicable law, we can reasonably accommodate applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs. Please take a moment to read this privacy notice carefully, as it describes what personal information London Stock Exchange Group (LSEG) (we) may hold about you, what it s used for, and how it s obtained, your rights and how to contact us as a data subject. If you are submitting as a Recruitment Agency Partner, it is essential and your responsibility to ensure that candidates applying to LSEG are aware of this privacy notice.

ประสบการณ์:

5 ปีขึ้นไป

ทักษะ:

Statistics, Finance, Risk Management

ประเภทงาน:

งานประจำ

• Bachelor s degree (or equivalent) degree in a quantitative field such as Data Science, Actuarial Science, Statistics, or Mathematics.
• 5+ years of related practical experience, preferably in commercial insurance sector.
• Solid understanding of insurance pricing principles, loss reserving, and risk assessment methodologies.
• Familiarity with insurance industry regulations, standards, and best practices.
• Develop and maintain loss cost models using GLMs and other advanced statistical techniques, incorporating relevant variables and factors for accurate pricing and risk assessment.
• Analyse historical insurance data to identify patterns and trends, and determine the impact of various factors on loss costs.
• Collaborate with underwriting, claims, and finance teams to understand business needs and provide data-driven insights for portfolio management.
• Conduct rate level reviews to ensure appropriate pricing of insurance products, considering risk exposure, market dynamics, and profitability goals.
• Enhance loss cost models over time by incorporating new data sources, refining variables,.
• and exploring innovative modelling techniques.
• Evaluate the impact of pricing strategies, policy changes, and market shifts on portfolio performance, and make recommendations for adjustments, if needed.
• Present findings and recommendations to stakeholders, including senior management and underwriting teams, in clear and concise reports.
• Work closely with other departments including Underwriting, Actuarial, and Risk Management, providing them with the data and insights needed to make evidence-based decisions.
• Functional Competency.
• Excellent analytical and problem-solving skills, with the ability to translate data into meaningful insights and recommendations.
• Strong communication skills to effectively convey complex findings and recommendations to both technical and non-technical stakeholders.
• Attention to detail and ability to work independently, managing multiple projects and deadlines efficiently.
• Strong proficiency in statistical modeling techniques, specifically GLMs, and experience with software tools like R, SAS, or Python.
• Proficiency with data analysis and visualisation tools and platforms, preferably Qliksense, Power BI, Alteryx, etc.
• Educational.
• Bachelor s degree (or equivalent) degree in a quantitative field such as Data Science, Actuarial Science, Statistics, or Mathematics.
• 5+ years of related practical experience, preferably in commercial insurance sector.
• Solid understanding of insurance pricing principles, loss reserving, and risk assessment methodologies.
• Familiarity with insurance industry regulations, standards, and best practices.
• Develop and maintain loss cost models using GLMs and other advanced statistical techniques, incorporating relevant variables and factors for accurate pricing and risk assessment.
• Analyse historical insurance data to identify patterns and trends, and determine the impact of various factors on loss costs.
• Collaborate with underwriting, claims, and finance teams to understand business needs and provide data-driven insights for portfolio management.
• Conduct rate level reviews to ensure appropriate pricing of insurance products, considering risk exposure, market dynamics, and profitability goals.
• Enhance loss cost models over time by incorporating new data sources, refining variables,.
• and exploring innovative modelling techniques.
• Evaluate the impact of pricing strategies, policy changes, and market shifts on portfolio performance, and make recommendations for adjustments, if needed.
• Present findings and recommendations to stakeholders, including senior management and underwriting teams, in clear and concise reports.
• Work closely with other departments including Underwriting, Actuarial, and Risk Management, providing them with the data and insights needed to make evidence-based decisions.
• Functional Competency.
• Excellent analytical and problem-solving skills, with the ability to translate data into meaningful insights and recommendations.
• Strong communication skills to effectively convey complex findings and recommendations to both technical and non-technical stakeholders.
• Attention to detail and ability to work independently, managing multiple projects and deadlines efficiently.
• Strong proficiency in statistical modeling techniques, specifically GLMs, and experience with software tools like R, SAS, or Python.
• Proficiency with data analysis and visualisation tools and platforms, preferably Qliksense, Power BI, Alteryx, etc.

ประสบการณ์:

5 ปีขึ้นไป

ทักษะ:

English

ประเภทงาน:

งานประจำ

• Organize training on products/services, scientific areas, brand and Divisional values, doctor-centric approach (SIMAC) and the medical, competitive, and regulatory environment.
• In charge of Medical Business Academy roll out and implementation, working in close collaboration with HR learning department.
• Define team objectives and follow-up, in line with Medical Management.
• Ensure training in internal and external with ethical standards regarding relations with health professionals.
• Upskills whole organization on medical topics.
• Bachelor s degree in major Pharmacy or Science (master s degree is a plus).
• Minimum 5 years in Sales/ Training Manager or management role in sales or marketing.
• Proficient in sales processes, skills, and techniques.
• Proven track record in creating and implementing training programs, particularly in sales training for teams and channel partners.
• Extensive technical product knowledge and strong business acumen.
• Experience in curriculum development, designing, implementation, and delivering both in-person and online training programs.
• Strong understanding of product specifications and competitive offerings.
• Ability to analyze training needs and conduct competitive analysis.
• Highly effective communication skills, both written and oral.
• Proficiency in English.
• Why us?
• We will support you through a tailor-made learning & development journey where you will receive constant career advice to empower you to navigate through and reach the Senior Leadership role of your dreams. Progressive leadership track - opportunities for growth & development.
• You can apply to up to three jobs within a rolling 30-day window.
• You cannot withdraw your application once you applied, so please make sure to choose a job that matches your dreams.
• Please visit "Your Application Space" to see the jobs you have already applied to.
• Please don t create another account with a different email. If you do so, your account might be merged and your application record will be deleted.