Data Scientist (Python, SQL, Azure)
Posted Updated
Summary
Data scientist at an education-tech company in Ho Chi Minh City, running data science projects end to end: translating business needs into data solutions, cleaning and exploring data, and building, evaluating and monitoring statistical/ML models. Core stack is Python, SQL and ML libraries, with cloud (Azure) exposure.
Top 3 Reasons To Join Us
Performance Bonus
Annual health check
Work from home 2 days a week.
The Job
Job Description
Your role and responsibilities:
- Participate in data science projects from problem definition through solution delivery.
- Analyze business requirements and translate them into data-driven solutions and actionable insights.
- Collect, clean, validate, and prepare structured and unstructured datasets for analysis.
- Perform exploratory data analysis (EDA) to identify trends, patterns, and opportunities.
- Develop, evaluate, and optimize statistical and machine learning models for prediction, classification, clustering, and other analytical tasks.
- Design and conduct experiments to evaluate hypotheses and measure model performance.
- Communicate findings and recommendations to stakeholders through reports, visualizations, and presentations.
- Collaborate with Product Owners, business stakeholders, and engineering teams to define project goals and data requirements.
- Monitor model performance, analyze results, and recommend improvements based on new data and business needs.
- Stay up to date with advances in data science, machine learning, and analytics methodologies.
Preferred qualifications:
- Passion for applying data science to solve real-world problems, particularly in the education domain.
- Experience developing predictive models or conducting research in education, learning analytics, or related fields.
- Experience analyzing and modeling learning behavior, educational, or user interaction data.
- Strong knowledge of statistics, probability, experimental design, and machine learning algorithms.
- Experience with the end-to-end data science lifecycle, including data collection, preprocessing, feature engineering, model development, evaluation, and deployment.
- Proficiency in Python and common data science libraries (e.g., Pandas, NumPy, Scikit-learn, TensorFlow, or PyTorch).
- Experience working with SQL and relational or NoSQL databases.
- Experience with data visualization tools and libraries (e.g., Matplotlib, Plotly, Tableau, or Power BI) is a plus.
- Familiarity with MLOps, model deployment, or cloud platforms is an advantage but not required.
- MS or PhD in Computer Science, Data Science, Statistics, Mathematics, or a related quantitative field.
Your Skills and Experience
- At least 3+ years of experience in data science or a related field, with strong programming skills in Python, R, or similar languages.
- Experience applying statistical analysis, machine learning, and predictive modeling to solve real-world business problems.
- Strong understanding of statistics, probability, hypothesis testing, experimental design (A/B testing), and data analysis techniques.
- Experience with the end-to-end data science lifecycle, including data collection, preprocessing, feature engineering, model development, evaluation, and interpretation.
- Experience working with SQL and relational or NoSQL databases.
- Experience working with cloud computing platforms (e.g., AWS, Azure, or Google Cloud) is preferred.
- Experience using large language models (LLMs) and generative AI for analytical or business applications is a plus.
- Familiarity with data visualization tools and libraries (e.g., Matplotlib, Plotly, Tableau, or Power BI) is an advantage.
- Excellent communication skills in English; proficiency in Japanese is a plus.
- Strong background in Statistics, Mathematics, Computer Science, Data Science, or a related quantitative discipline.
- Passion for continuous learning and staying current with advances in data science, machine learning, and AI.
- Strong analytical thinking and problem-solving skills, with the ability to translate business requirements into data-driven insights and predictive models.
- Ability to communicate complex analytical findings effectively to both technical and non-technical stakeholders.
- A collaborative team player who is willing to support colleagues and work effectively in cross-functional teams.
- Flexible and adaptable, with the ability to contribute to different phases of a data science project as needed.
Why You'll Love Working Here
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