Data Scientist - TEKsystems

Allegis Group Singapore Pte Ltd; Singapore; On-site; SGD 80,000 - 140,000; Full time

Job summary

Allegis Group Singapore Pte Ltd is seeking a Data Scientist to join a growing global technology team. The role focuses on applying data science and quality management to improve the accuracy and integrity of large-scale search and ML recommender systems used by millions worldwide.

You will design data quality metrics, build self-serve dashboards, and develop Python-based solutions to process and enhance data reliability, collaborating with global operations and data engineering teams to drive

Qualifications

• Strong analytical and statistical skills with data quality or data science experience.
• Proficiency in Python (Pandas, NumPy, Scikit-learn) and SQL.
• Experience with data visualization tools like Tableau or Power BI.
• Knowledge of quality assurance principles and risk identification.
• Excellent communication and ownership mindset.
• Experience building self-serve tools or web apps using Python frameworks (Flask, Streamlit, Spark) is a plus.
• Exposure to advanced statistical models and ML algorithms is advantageous.

Responsibilities

• Design and implement data quality metrics, sampling methods, and audit frameworks.
• Perform statistical analysis to identify anomalies and ensure rating accuracy.
• Build automation tools and self-serve dashboards for quality checks.
• Collaborate with global operations and data engineering teams.
• Develop Python-based solutions to process, evaluate, and improve data reliability.

Skills

Analytical skills

Statistical analysis

Python

SQL

Data visualization

Quality management

Communication

Tools

Pandas

NumPy

Scikit-learn

Tableau

Power BI

Flask

Streamlit

Spark

Job description

We are looking for a Data Scientist to join a growing team within a global technology organisation. This role focuses on using data science and quality management techniques to improve the accuracy and integrity of large-scale search and machine learning recommendation systems impacting millions of users world-wide.

The ideal candidate is passionate about data quality, risk assessment, and automation, and enjoys building tools that make processes smarter and more efficient.

Key Responsibilities

• Design and implement data quality metrics, sampling methods, and audit frameworks.
• Conduct statistical analysis to identify anomalies and ensure rating accuracy
• Build automation tools and self-serve dashboards to streamline quality checks.
• Collaborate closely with global operations and data engineering teams.
• Develop Python-based solutions to process, evaluate, and improve data reliability.

Requirements

• Strong analytical and statistical skills, with experience in data quality management or data science.
• Proficiency in Python (Pandas, NumPy, Scikit-learn) and SQL for data querying and analysis.
• Experience with data visualization (Tableau, Power BI, or similar).
• Knowledge of quality assurance principles and risk identification.
• Excellent communication skills and a strong sense of ownership
• Experience developing self-serve tools or web applications using Python frameworks (e.g. Flask, Streamlit, Spark) is preferred
• Exposure to advanced statistical models (Bayesian analysis, survival analysis, etc.) and advanced machine learning algorithms (e.g., decision trees, clustering, time-series forecasting) is an advantage.