Data Analytics Engineer: ML Pipelines & Insights

Strides Digital Pte. Ltd.; Singapore; On-site; SGD 70,000 - 110,000; Full time

Job summary

Stride Digital Pte. Ltd. in Singapore is seeking a Data Analytics Engineer to lead data pipelines, analyze data, and develop ML/AI models to enhance data capabilities across the organization.

You will work with data scientists to translate requirements into scalable solutions, build dashboards, and publish research with potential for future productization. A strong foundation in statistics, ML, and data visualization is essential.

Qualifications

• Graduate or postgraduate in statistics, data science, or mathematics.
• 2+ years in data analytics/insights or demonstrable equivalent skills.
• Ability to analyze complex datasets and extract meaningful insights.
• Experience with ML models and end-to-end deployment.
• Knowledge of data warehousing, ETL, and data schemas.
• Familiarity with applied statistics and ML algorithms in industry use cases.

Responsibilities

• Dissect large data volumes and perform descriptive/diagnostic analysis.
• Develop statistical and ML models; conduct simulations for data monetization.
• Build data pipelines integrating diverse sources for analytics.
• Collaborate with data scientists to translate requirements into scalable solutions.
• Design interactive dashboards and reports communicating findings clearly.
• Collaborate with academia on research topics with productization potential.

Skills

Descriptive analysis

Diagnostic analysis

Statistical modeling

Machine learning

Data visualization

Python

SQL

R

Data analysis at scale

Pattern discovery

Education

Bachelor’s degree or Postgraduate degree in Statistics, Data Science, Mathematics or equivalent

Tools

Tableau

PowerBI

Python libraries (scikit-learn, etc.)

Docker

Job description

Stride Digital Pte. Ltd. in Singapore is seeking a Data Analytics Engineer to lead data pipelines, analyze data, and develop ML/AI models to enhance data capabilities across the organization.

You will work with data scientists to translate requirements into scalable solutions, build dashboards, and publish research with potential for future productization. A strong foundation in statistics, ML, and data visualization is essential.