Senior Data Science Specialist
Job Description
As a Senior Data Scientist, you will play a key role in delivering high-impact analytics and machine learning solutions at scale for a leading telecom operator. You’ll work on complex, real-world problems, influence business decisions, and help shape how advanced analytics is embedded across the organisation.
This role offers hands-on ownership, exposure to senior stakeholders, and the opportunity to grow into broader technical or leadership responsibilities.
Responsibilities
- Lead the development and delivery of advanced analytics and machine learning models to address key business opportunities and gaps.
- Translate ambiguous business problems into well-structured analytical approaches and recommend appropriate modelling techniques.
- Partner with business stakeholders with minimal supervision, clearly communicating insights, assumptions, and model outcomes.
- Collaborate with peers across data science, engineering, and analytics teams on cross-functional problem solving.
- Continuously enhance models through feature engineering, new data sources, and experimentation to improve business performance.
- Contribute to setting best practices, standards, and re-usable assets across the data science team.
Requirements
- Bachelor’s degree in Data Science, Actuarial Science, Mathematics, Statistics, Computer Science, or related fields.
- Strong, demonstrable experience delivering analytics and machine learning projects end-to-end.
- Experience in the telecommunications industry is an advantage but not mandatory.
- Hands-on experience with Python, SQL, R (or equivalent) and big data / distributed processing tools (e.g. Spark).
- Working knowledge of machine learning algorithms and classifiers.
- Strong communication, presentation, and analytical skills, with the ability to influence non-technical stakeholders.
Job Description
As a Senior Data Scientist, you will play a key role in delivering high-impact analytics and machine learning solutions at scale for a leading telecom operator. You’ll work on complex, real-world problems, influence business decisions, and help shape how advanced analytics is embedded across the organisation.
This role offers hands-on ownership, exposure to senior stakeholders, and the opportunity to grow into broader technical or leadership responsibilities.
Responsibilities
- Lead the development and delivery of advanced analytics and machine learning models to address key business opportunities and gaps.
- Translate ambiguous business problems into well-structured analytical approaches and recommend appropriate modelling techniques.
- Partner with business stakeholders with minimal supervision, clearly communicating insights, assumptions, and model outcomes.
- Collaborate with peers across data science, engineering, and analytics teams on cross-functional problem solving.
- Continuously enhance models through feature engineering, new data sources, and experimentation to improve business performance.
- Contribute to setting best practices, standards, and re-usable assets across the data science team.
Requirements
- Bachelor’s degree in Data Science, Actuarial Science, Mathematics, Statistics, Computer Science, or related fields.
- Strong, demonstrable experience delivering analytics and machine learning projects end-to-end.
- Experience in the telecommunications industry is an advantage but not mandatory.
- Hands-on experience with Python, SQL, R (or equivalent) and big data / distributed processing tools (e.g. Spark).
- Working knowledge of machine learning algorithms and classifiers.
- Strong communication, presentation, and analytical skills, with the ability to influence non-technical stakeholders.
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