เงื่อนไขการค้นหา

ประสบการณ์:

2 ปีขึ้นไป

ทักษะ:

Python, SQL, Tableau, Quantitative Analysis

ประเภทงาน:

งานประจำ

• Understanding of business problems forgathering/analyzing/designing the data to solve the problems from end-to-end process.
• Excellent in written and verbal communication skills for coordinating across teams.
• Analyze large amounts of information to discover trends and patterns.
• Lead the analytics group in management of projects and experiment designing, implementing innovative Predictive Models, implementing innovative analytic solutions or driving outstanding results.
• Proficient in common data science toolkits (R, Python) and using SQL languages.
• Experience using business intelligence tools (e.g. Tableau) and data frameworks (e.g. Hadoop).
• Good applied statistics skills, such as distributions, statistical testing, regression, etc.
• At least 2-3 year in Business Intelligence/Data Analytic.
• Proficiency in statistical analysis, quantitative analytic, forecasting/predictive analytic, experimental design and optimization algorithms.
• Technical expertise regarding data modeling, data mining, segmentation techniques, unstructured data skills, and other data science.
• Programming skills in big data frameworks and statistical modeling such as SAS, R, and Python, CE Techniques.
• Experience in data visualization tools.
• Knowledge/experience in machine learning.
• Domain knowledge of mobile, network and telecommunication technology and services would be advantageous.

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:

8 ปีขึ้นไป

ทักษะ:

Product Development, GMP, English

ประเภทงาน:

งานประจำ

• Deliver a compliant Thailand Healthcare business.
• Collaborate with Thailand leadership team on broad business & organization matters.
• Lead local registration strategy and planning for base business & new product development to support business objectives and deliver timely approvals.
• Build and maintain robust network with regulatory authorities. Engage them in timely manner to ensure smooth approvals.
• To ensure a robust submission dossier meeting the most current requirements is prepared in a timely manner.
• Manage internal & external approval process of new pack materials, POSM and advertisement materials.
• Ensure all relevant regulatory systems and databases are maintained up to date.
• Actively participate in cross functional meetings or coordination meetings for projects regionally and globally.
• To stay updated with the upcoming changes in regulatory legislation and guidelines and define impact to business.
• Negotiate and take a lead in driving long term external advocacy in partnership with Government Relations and relevant industry associations.
• Job Qualifications.
• Graduate with degree (Bachelors/Masters) in Pharmacy. Registered pharmacist is required.
• Having minimum 8 years experience in regulatory associated with Consumer Health products. Extended experience and knowledge with focus on OTC medicines and health supplements will be advantageous.
• Demonstrated experience dealing with and influencing related government agencies, i.e.: Thai FDA towards successful regulatory outcomes.
• Knowledge and experience in GMP, GDP regulations will be an advantage.
• Communication Skills - Able to clearly present information to non-technical leadership teams through the spoken word. Able to write and speak clearly and effectively in English to the team.
• Decision Making & Problem Solving - Able to take action in solving problems while exhibiting judgement and a realistic understanding of issues, able to use reason, even when dealing with emotional topics.
• Policy and Procedures - Able to relate to routine operations in a manner that is consistent with established policies and procedures.
• Analytical Skills - Able to use a systematic approach in solving problems through analysis of problem and evaluation of alternate solutions.
• Proficient in English- both written and oral.
• Proficient in Computer systems.
• Job Schedule.
• Full time
• Job Number.
• R000118013
• Job Segmentation.
• Experienced Professionals (Job Segmentation)

ทักษะ:

Automation

ประเภทงาน:

งานประจำ

• Lead cross-functional projects using data modeling and analysis techniques to discover insights that will guide strategic decisions and uncover optimization opportunities.
• Build, develop and maintain data models, reporting systems, data automation systems, dashboards and performance metrics to support key business decisions.
• Examine, interpret and report results of analytical initiatives to management, product, marketing and sales team.
• We're committed to bringing passion and customer focus to the business. If you like wild growth and working with happy, enthusiastic over-achievers, you'll enjoy your career with us.

ทักษะ:

Research, Statistics, Python, English

ประเภทงาน:

งานประจำ

• Apply statistical and machine learning methods to large, complex data sets to draw insights and provide actionable recommendations.
• Solve complex problems on both technical and business sides using advanced analytical methods.
• Work with Engineering teams to implement end-to-end process from model development to testing, validation, and deployment.
• Research and develop new quantitative models and frameworks to enhance the company s data science capability.
• Basic Qualifications Bachelor s degree in Engineering, Computer Science, Math, Physics, Statistics or other areas that are highly quantitative.
• Experience with statistical programming languages (e.g., Python, R, pandas) and database software (e.g., SQL, PySpark).
• Knowledge in statistics (e.g., hypothesis testing, regression) and machine learning.
• Strong analytical problem-solving capabilities.
• Preferred Qualifications Master s or PhD degree in a quantitative discipline.
• Experience applying machine learning and statistical methods to large datasets.
• Solid understanding of advanced statistics and machine learning practices.
• Experience in one or more specialized machine learning areas (e.g., NLP, deep learning, recommendation systems, reinforcement learning).
• Outstanding coding skills or software development background.
• Ability to think independently and communicate complex ideas to less technical persons.
• Excellent command of English in both verbal and written forms.
• We're committed to bringing passion and customer focus to the business. If you like wild growth and working with happy, enthusiastic over-achievers, you'll enjoy your career with us.

ประสบการณ์:

4 ปีขึ้นไป

ทักษะ:

Statistics, Python, SQL

ประเภทงาน:

งานประจำ

• Collaborate with cross-functional teams to identify and prioritize business opportunities that can be addressed through data-driven solutions.
• Extract insights from large and complex datasets using a variety of tools and techniques.
• Develop and deploy predictive models and algorithms using statistical AI/machine learning, deep learning and generative AI modeling.
• Present findings and recommendations to stakeholders in a clear and compelling manner.
• Implement data-driven solutions in various environments, including integration with existing systems and processes.
• Stay up to date on the latest development in data science and bring new idea and technology to the team.
• Monitor the performance of deployed models together with algorithms and continuously improve model accuracy over time.
• Bachelor s or Master s degree in data science, Computer Science, Statistics, or related field.
• 4+ years of experience as a Data Scientist, with a focus on industries.
• Descriptive Analytics.
• Predictive & Prescriptive Analytics (Machine learning, Forecasting, Optimization, choosing the best path).
• Strong programming skills in Python and SQL along with libraries and frameworks for machine learning and statistical test, and their variation among databases.
• Experience with statistical and machine learning techniques.
• Proficiency in optimizing large, complicated SQL statements and code versioning tools such as Git, Mercurial, SVN or others.
• Experience with data visualization tools such as Looker Studio, Tableau, and Power BI.
• Strong problem-solving and communication skills.
• Experience with Cloud technology and databases (Cloud AWS, Azure, GCP).
• Extensive knowledge of Customer relationship management, Customer experience, Next best action, Credit scoring, and Insight & pattern discovery.
• Location: True Digital Park, Bangkok.

ประสบการณ์:

2 ปีขึ้นไป

ทักษะ:

Research, Python, SQL

ประเภทงาน:

งานประจำ

• Develop machine learning models such as credit model, income estimation model and fraud model.
• Research on cutting-edge technology to enhance existing model performance.
• Explore and conduct feature engineering on existing data set (telco data, retail store data, loan approval data).
• Develop sentimental analysis model in order to support collection strategy.
• Bachelor Degree in Computer Science, Operations Research, Engineering, or related quantitative discipline.
• 2-5 years of experiences in programming languages such as Python, SQL or Scala.
• 5+ years of hands-on experience in building & implementing AI/ML solutions for senior role.
• Experience with python libraries - Numpy, scikit-learn, OpenCV, Tensorflow, Pytorch, Flask, Django.
• Experience with source version control (Git, Bitbucket).
• Proven knowledge on Rest API, Docker, Google Big Query, VScode.
• Strong analytical skills and data-driven thinking.
• Strong understanding of quantitative analysis methods in relation to financial institutions.
• Ability to clearly communicate modeling results to a wide range of audiences.
• Nice to have.
• Experience in image processing or natural language processing (NLP).
• Solid understanding in collection model.
• Familiar with MLOps concepts.