What a Data Scientist Does:
- Lead, execute, and deliver end-to-end data science initiatives for financial services clients in Thailand.
- Develop detailed project scopes, analytical methodologies, and design and implement solutions using appropriate tools and techniques.
- Ensure high standards of quality control and maintain comprehensive, up-to-date documentation across all data science projects.
- Analyze client portfolio growth, uncover spending patterns, and identify growth opportunities using alternative data sources and advanced modeling approaches.
- Provide analytical support for card and customer campaigns, including customer segmentation, design and maintenance of test-and-control frameworks, and tracking campaign effectiveness for both ongoing and tactical initiatives.
- Benchmark portfolio performance against market trends to identify gaps, optimization areas, and opportunities for uplift using internal and client data.
- Continuously track and enhance portfolio dashboards, focusing on market segments and channel performance, and deliver data-driven insights to improve campaign outcomes.
- Advance analytical capabilities by introducing new data science methodologies, tools, and best practices.
- Contribute to thought leadership in data science by driving innovation and developing reusable intellectual assets.
- Manage communications effectively with clients and internal stakeholders.
- Champion data-driven decision-making within partner organizations by advising, mentoring analytical teams, and sharing best practices and case studies.
What You Will Need:
- A degree in a quantitative discipline such as Statistics, Mathematics, Operations Research, Computer Science, Economics, or Engineering; a Master's or Ph.D. is an advantage.
- At least 5 years of relevant experience in data exploration, modeling, and feature engineering.
- Strong knowledge of statistical and machine learning techniques, including Neural Networks, Gradient Boosting, Linear and Logistic Regression, Decision Trees, Random Forests, Markov Chains, Support Vector Machines, Clustering, Principal Component Analysis, Factor Analysis, and related methods.
- Proficiency in programming and query languages such as Python, along with experience using data analysis and management tools including SQL, DBeaver, and Power BI.
- Ability to translate complex analytical findings into clear, actionable insights that drive growth and performance improvement.
- Proven experience managing multiple analytics projects simultaneously while collaborating with cross-functional stakeholders.
- Strong stakeholder management skills with a collaborative, diplomatic, and adaptable working style.
- Excellent communication and presentation skills, with the ability to clearly convey complex concepts both verbally and in writing.
- Expertise in data storytelling and visualization, with strong skills in MS Excel and MS PowerPoint.
- Good understanding of local market dynamics and relevant industry regulations.
Desired Skills and Experience
Data Science, Advanced Analytics, Statistical Modeling, Machine Learning, Feature Engineering, Predictive Modeling, Customer Segmentation, Campaign Analytics, Test & Control Design, Portfolio Performance Analysis, Growth Analytics, Data Exploration, Data Visualization, Data Storytelling, Python, SQL, Power BI, DBeaver, Dashboard Development, Neural Networks, Gradient Boosting, Regression Analysis, Decision Trees, Random Forests, Support Vector Machines, Clustering, Principal Component Analysis (PCA), Factor Analysis, Time Series Analysis, Model Performance Tracking, Market Benchmarking, Financial Services Analytics, Card & Payment Analytics, Stakeholder Management, Cross-Functional Collaboration, Business Insight Generation, Communication & Presentation Skills, Excel, PowerPoint, Regulatory Awareness, Thought Leadership, Best Practice Development
Argyll Scott Asia is acting as an Employment Business in relation to this vacancy.
