Data Scientist

About ADA

ADA is a leading data and artificial intelligence (AI) company that designs and executes integrated digital, analytics, and marketing solutions. We operate in 12 markets in Asia and partner with leading brands to drive their data and digital maturity.

Role Overview

We are seeking a skilled Data Scientist with robust expertise in Machine Learning and Artificial Intelligence. This role involves designing, developing, and deploying scalable data-driven solutions. The ideal candidate will possess hands-on experience in building predictive models, analyzing extensive datasets, and applying AI/ML techniques to resolve complex business challenges.

Key Responsibilities

• Develop and implement machine learning models and AI solutions for business challenges.
• Perform comprehensive data cleaning, feature engineering, and exploratory data analysis (EDA) on large structured and unstructured datasets.
• Construct predictive models utilizing techniques such as regression, classification, clustering, Natural Language Processing (NLP), and deep learning.
• Deploy models into production environments adhering to MLOps best practices.
• Collaborate effectively with data engineers, product managers, and business stakeholders to translate requirements into actionable technical solutions.
• Monitor model performance, continuously optimizing and retraining models as needed.
• Leverage cloud platforms and big data tools for efficient and scalable data processing.
• Present data-driven insights and recommendations through compelling data visualization and storytelling.

• Python / R
• SQL

• Supervised & Unsupervised Learning
• Feature Engineering
• Model Evaluation Techniques
• Model Optimization

• Natural Language Processing (NLP)
• Deep Learning (TensorFlow / PyTorch)
• Generative AI (LLMs, Prompt Engineering – preferred)

• Pandas, NumPy, Scikit-learn
• Spark / PySpark (preferred)

• Power BI / Tableau / Matplotlib / Seaborn

• AWS / Azure / GCP (any one preferred)

• Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Mathematics, or a related field.
• 2–5 years of hands-on experience in Machine Learning and AI projects.
• Demonstrated experience working with large datasets and addressing real-world business problems.

• Experience with MLOps and model deployment methodologies.
• Familiarity with containerization technologies like Docker and orchestration tools like Kubernetes.
• Experience with Large Language Models (LLMs), Generative AI, or AI agents.
• A strong foundational understanding of statistics and probability.

• Exceptional problem-solving capabilities.
• Excellent communication and stakeholder management skills.
• Ability to thrive in a dynamic and fast-paced Agile environment.