AIS is seeking a Data Scientist to join our dynamic team in Bangkok, Thailand. This role involves working with massive datasets, primarily on cloud infrastructure, to support advanced analytics and machine learning applications. At AIS, you’ll tackle diverse and impactful use cases across multiple business domains, including the mobile phone business, high-speed home broadband, entertainment, and media, gaining exposure to some of the most exciting and complex data challenges in the industry.

Qualifications

Data Science & Analytics

• Data Science Foundations: Strong foundation in data science, statistics, and advanced data analytics, including data visualization to communicate insights effectively.
• Exploratory Data Analysis (EDA): Skilled in performing EDA to uncover patterns, detect anomalies, and generate meaningful insights from data.
• Experimentation & Testing: Skilled in designing A/B tests or other experimental designs to measure business impact, analyze results, and communicate findings clearly to stakeholders.

Machine Learning & AI

• Model Development & Deployment: Experience in building, deploying, and optimizing machine learning models on large datasets.
• Generative AI (GenAI): Opportunity to work on GenAI projects that drive innovation and impactful business solutions.

Problem-Solving & Collaboration

• Analytical & Problem-Solving Skills: Strong analytical and problem-solving abilities focused on deriving actionable insights from data.
• Team Collaboration: Ability to work effectively both independently and as part of a collaborative team, contributing to shared project goals.

Technical Expertise

• Proficiency in Big Data Technologies: Expertise in Spark, PySpark, and SQL for large-scale data processing focused on feature creation for machine learning models and data analysis tasks.
• Programming Skills: Strong proficiency in Python for data analysis and machine learning (including libraries like Pandas, PySpark, Scikit-learn, XGBoost, LightGBM, Matplotlib, Plotly, Seaborn, etc.).
• Python Notebooks: Familiarity with Jupyter, Google Colab, or Apache Zeppelin for interactive data analysis and model development.
• Platform Experience: Experience in using PySpark on cloud platforms such as Azure Databricks or other platforms (including on-premise) is a plus.

Education & Experience

• Educational Background: Bachelor’s or advanced degree in Data Science, Statistics, Computer Science, Computer Engineering, Mathematics, Information Technology, Engineering, or related fields.
• Work Experience: At least 2-3 years of relevant experience in Data Science, Analytics, or Machine Learning, with demonstrated technical expertise and a proven track record of driving data-driven business solutions.