Data Scientist
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Job Location:
Cape Town - South Africa
Monthly Salary:
Not Disclosed
Posted on:
11 hours ago
Vacancies:
1 Vacancy
Job Summary
JOB DESCRIPTION
Title: Senior Data Scientist
Location: France Dubai or Remote
Title: Senior Data Scientist
Location: France Dubai or Remote
COMPANY OVERVIEW
Our clients are one of the worlds largest Communications Service Providers (CSPs).Whose software monitors and
optimises the networks of eight of the top 10 global telecom groups ensuring resilience for over 2 billion subscribers worldwide.
Were entering an era of predictive analytics Generative AI and agent-based intelligence allowing us to redefine how networks are managed
and automated.
At our clients youll work with a global diverse team of innovators passionate about turning
data into intelligence
Our clients are one of the worlds largest Communications Service Providers (CSPs).Whose software monitors and
optimises the networks of eight of the top 10 global telecom groups ensuring resilience for over 2 billion subscribers worldwide.
Were entering an era of predictive analytics Generative AI and agent-based intelligence allowing us to redefine how networks are managed
and automated.
At our clients youll work with a global diverse team of innovators passionate about turning
data into intelligence
Overview
We are seeking a highly skilled Senior Data Scientist to lead the design and
implementation of advanced analytical and machine learning models that enable
predictive prescriptive and automated intelligence. The ideal candidate will have deep
expertise in data modelling forecasting and anomaly detection along with the ability to
design scalable solutions that transform complex datasets into actionable insights. The
role also includes exposure to Generative AI techniques such as LLMs RAG and
intelligent agents that support enhanced analytics and decision automation.
We are seeking a highly skilled Senior Data Scientist to lead the design and
implementation of advanced analytical and machine learning models that enable
predictive prescriptive and automated intelligence. The ideal candidate will have deep
expertise in data modelling forecasting and anomaly detection along with the ability to
design scalable solutions that transform complex datasets into actionable insights. The
role also includes exposure to Generative AI techniques such as LLMs RAG and
intelligent agents that support enhanced analytics and decision automation.
Key Responsibilities
1. Machine Learning & Predictive Analytics
Develop and deploy machine learning models for forecasting anomaly detection
optimization and root cause analysis.
1. Machine Learning & Predictive Analytics
Develop and deploy machine learning models for forecasting anomaly detection
optimization and root cause analysis.
Conduct data exploration and pattern analysis to identify trends correlations and
behavioural deviations.
Apply statistical and algorithmic approaches to improve model performance and
interpretability.
Validate and monitor models to ensure precision scalability and business
relevance.
2. Data Preparation & Feature Engineering
Work with data engineering teams to establish robust data pipelines and
integration frameworks.
Develop processes for data cleaning transformation correlation and feature
extraction.
Ensure data consistency quality and traceability across multiple systems and
domains.
Implement automated workflows to maintain high data integrity and modeling
efficiency.
3. Analytical Insight & Decision Enablement
Translate complex analytical outcomes into clear actionable insights that guide
decision-making.
behavioural deviations.
Apply statistical and algorithmic approaches to improve model performance and
interpretability.
Validate and monitor models to ensure precision scalability and business
relevance.
2. Data Preparation & Feature Engineering
Work with data engineering teams to establish robust data pipelines and
integration frameworks.
Develop processes for data cleaning transformation correlation and feature
extraction.
Ensure data consistency quality and traceability across multiple systems and
domains.
Implement automated workflows to maintain high data integrity and modeling
efficiency.
3. Analytical Insight & Decision Enablement
Translate complex analytical outcomes into clear actionable insights that guide
decision-making.
Collaborate with product and domain experts to identify opportunities for data-
driven improvement.
driven improvement.
Build dashboards and visualizations that communicate model results and
performance trends effectively.
Quantify the impact of data science initiatives and align with measurable business
KPIs.
4. Model Deployment & Lifecycle Management
Deploy and maintain ML models using MLOps pipelines with continuous
retraining and performance tracking.
Implement model monitoring version control and drift detection frameworks.
Collaborate with DevOps and application teams to integrate analytics
components into production environments.
performance trends effectively.
Quantify the impact of data science initiatives and align with measurable business
KPIs.
4. Model Deployment & Lifecycle Management
Deploy and maintain ML models using MLOps pipelines with continuous
retraining and performance tracking.
Implement model monitoring version control and drift detection frameworks.
Collaborate with DevOps and application teams to integrate analytics
components into production environments.
Ensure models comply with quality governance and reliability standards.
5. Generative AI & Intelligent Systems
Apply LLM and RAG-based architectures for knowledge retrieval contextual
reasoning and data summarization.
Develop AI-driven agents that support analytical workflows and decision
automation.
Experiment with prompt engineering and fine-tuning to enhance model accuracy
and adaptability.
Combine predictive modelling with generative techniques to enrich data insights
and usability.
5. Generative AI & Intelligent Systems
Apply LLM and RAG-based architectures for knowledge retrieval contextual
reasoning and data summarization.
Develop AI-driven agents that support analytical workflows and decision
automation.
Experiment with prompt engineering and fine-tuning to enhance model accuracy
and adaptability.
Combine predictive modelling with generative techniques to enrich data insights
and usability.
Qualifications
Masters or Ph.D. in Data Science Computer Science Statistics Mathematics or
related quantitative field.
7 years of experience in machine learning AI or advanced analytics with proven
impact in model deployment.
Strong programming proficiency in Python R and SQL with experience using
TensorFlow or PyTorch.
Expertise in data modeling forecasting classification clustering and
optimization.
Proficiency in data wrangling (pandas NumPy PySpark) and visualization tools
(Power BI Tableau Plotly).
Knowledge of MLOps practices cloud environments (AWS Azure GCP) and
model performance monitoring.
Strong foundation in statistics probability and hypothesis testing.
Masters or Ph.D. in Data Science Computer Science Statistics Mathematics or
related quantitative field.
7 years of experience in machine learning AI or advanced analytics with proven
impact in model deployment.
Strong programming proficiency in Python R and SQL with experience using
TensorFlow or PyTorch.
Expertise in data modeling forecasting classification clustering and
optimization.
Proficiency in data wrangling (pandas NumPy PySpark) and visualization tools
(Power BI Tableau Plotly).
Knowledge of MLOps practices cloud environments (AWS Azure GCP) and
model performance monitoring.
Strong foundation in statistics probability and hypothesis testing.
Experience with telecom network assurance or large-scale telemetry datasets.
Familiarity with LLM and RAG implementations vector databases and LangChain
frameworks.
Familiarity with LLM and RAG implementations vector databases and LangChain
frameworks.
Understanding of AIOps network analytics and closed-loop automation.
Proven ability to bridge data science and business strategy through measurable
outcomes.
Proven ability to bridge data science and business strategy through measurable
outcomes.
Required Experience:
IC
About Company
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