Data Scientist & Engineer: Scale Insights with ML

KewMann Pte Ltd

Singapore

On-site

SGD 70,000 - 110,000

Full time

12 days ago
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Job summary

KewMann Pte Ltd in Singapore is seeking a data scientist/data engineer who thrives on learning, data, scale and agility. You will extract insights from highly complex data sets and design scalable prediction algorithms to support business decisions.

Responsibilities include analyzing raw data, cleansing and structuring for downstream processing, and generating actionable insights to drive improvements. The role requires collaboration across teams and fluency in Python or SQL.

Qualifications

  • Bachelor's degree or equivalent experience in a quantative field (Statistics, Mathematics, Computer Science, Engineering, etc.)
  • 1 to 5 years' of experience in data science and/or data engineering
  • Deep understanding of predictive modeling, machine-learning, clustering and classification techniques, and algorithms
  • Fluency in a programming language (Python, SQL)
  • Knowledge of knowledge graph & LLMs will be advantageous
  • Familiarity with Big Data frameworks and visualization tools (Hadoop, Spark, Superset, Hive)
  • Experience in data governance implementation or practices (data security, data quality and metadata management) are highly desired

Responsibilities

  • Analyze raw data: assessing quality, cleansing, structuring for downstream processing
  • Design accurate and scalable prediction algorithms
  • Generate actionable insights for business improvements

Skills

Data analysis
Predictive modeling
Machine learning
Python
SQL
Big Data tools
Data governance

Education

Bachelor's degree or equivalent in quantitative field

Tools

Hadoop
Spark
Superset
Hive

Job description

KewMann Pte Ltd in Singapore is seeking a data scientist/data engineer who thrives on learning, data, scale and agility. You will extract insights from highly complex data sets and design scalable prediction algorithms to support business decisions.

Responsibilities include analyzing raw data, cleansing and structuring for downstream processing, and generating actionable insights to drive improvements. The role requires collaboration across teams and fluency in Python or SQL.

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