Data Scientist

EDOTCO Group; Selangor; On-site; MYR 72,000 - 108,000; Full time

Job summary

EDOTCO Group is seeking a Senior Data Scientist to enhance network planning through advanced analytics and machine learning. The ideal candidate will analyze geospatial data, support decision-making processes, and collaborate with engineering and operational teams to drive business objectives.

Qualifications

• 2+ years of experience in data science with a focus on geospatial data.
• Familiarity with geospatial libraries and machine learning algorithms.
• Strong problem-solving skills and business awareness.

Responsibilities

• Develop machine learning models for network planning.
• Conduct geospatial analyses and collaborate with various teams.
• Present data findings and support ETL processes.

Skills

Python

PySpark

Geospatial analysis

Analytical Thinking

Problem-solving

Education

Bachelor’s degree in Data Science

Master’s degree (related field)

Tools

GeoPandas

QGIS

AWS

SQL

Job description

Job Purpose

The Senior Data Scientist will contribute to the analysis and optimization of network and planning strategies within the EDOTCO Group, focusing on geospatial data. This role involves applying advanced analytics and machine learning techniques to develop insights, support predictive modelling, and improve decision-making. The Data Scientist will work closely with team members to deliver valuable, data-driven solutions that enhance network efficiency and contribute to business objectives.

Key Accountabilities

Data Analysis & Modelling

• Assist in developing machine learning models to support network planning and performance analysis, with an emphasis on geospatial data.
• Conduct geospatial analyses using tools like GeoPandas and QGIS to understand location-based trends and make recommendations.

Collaboration & Communication

• Work with engineering, operations, and strategy teams to translate technical insights into actionable business solutions.
• Collaborate with vendors and external partners to integrate geospatial tools and ensure alignment with data infrastructure needs.

Machine Learning & Data Processing

• Contribute to the implementation of machine learning models to identify network gaps and optimize resource allocation.
• Support ETL processes for large geospatial datasets, maintaining data quality and processing efficiency.
• Utilize AWS Bedrock to access and integrate foundation models for generative AI applications, enhancing the scalability and security of AI solutions.

Reporting & Insights

• Present data findings to non-technical stakeholders, explaining insights in an accessible and actionable format.
• Provide performance metrics to monitor the impact of analytics on network and business goals.

Continuous Learning

• Stay informed on advancements in machine learning, AI, and geospatial tools, and contribute new ideas for business applications.
• Participate in the ongoing evaluation and optimization of models to ensure accuracy and relevance.

Qualification, Skills & Experience

• Bachelor’s degree or higher in Data Science, Computer Science, Statistics, or a related field.
• 2+ years of experience in data science, preferably with exposure to geospatial data and network analytics.
• Proficiency in Python & PySpark, including familiarity with geospatial libraries like GeoPandas and machine learning libraries.
• Basic experience with SQL and cloud environments (e.g., AWS, GCP) is a plus.
• Understanding of geospatial analytics and its role in network planning.
• Knowledge of machine learning algorithms and techniques for spatial data analysis.
• Familiarity with generative AI models and their applications in data analysis.
• Strong problem-solving skills and the ability to communicate technical insights to non-technical audiences.
• Analytical Thinking: Ability to break down complex data and find patterns to guide decision-making.
• Business Awareness: Understanding of the telecommunications industry and ability to apply analytics to improve network planning.
• Team Collaboration: Ability to work effectively with team members and stakeholders to achieve shared goals.
• Adaptability: Willingness to learn and apply new tools, methods, and approaches as needed.
• Shows commitment to high-quality standards, continuous improvement, and ethical practices.
• Known for strong analytical skills and geospatial data insights, offering valuable contributions to network and planning analytics.