Data Scientist developing advanced analytical solutions for Kantar's Global Data Science and Innovation team. Collaborating on AI/ML projects to enhance organizational growth.
About the role
- Data Scientist at Vodafone developing advanced analytical models to derive insights from large datasets. Collaborating on AI systems within cloud environments focusing on business outcomes.
Responsibilities
- Work with large-scale datasets and apply modern data practices across ingestion, transformation, governance, security, and privacy in both on-premises and cloud environments (AWS preferred)
- Influence and contribute to innovative approaches that extract value from enterprise-wide and external data sources
- Build diagnostic models using decision theory and causal techniques such as probability, DAG, ADMG, deterministic SME, and other causal frameworks to improve insight-led decisions
- Productise diagnostic systems for scalability, reuse, and integration into business workflows
- Develop predictive and prescriptive analytics models using ML, DL, NLP, reinforcement learning, and expert systems
- Build scalable and real‑time prescriptive learning systems that determine the “Next Best Action” for operational decision-making
- Create autonomous cognitive systems that prescribe proactive actions, leverage ML predictions, and incorporate feedback with minimal human intervention
- Apply advanced deep‑learning architectures such as CNNs, RNNs, MLPs, and other neural networks
- Use ML and DL libraries and frameworks including TensorFlow, PyTorch, Scikit‑learn, NumPy, Pandas, Statsmodels, Theano, and XGBoost
- Utilise programming languages such as Python, R, and SQL to support modelling and automation tasks
- Develop insights using visualisation platforms such as Tableau and Power BI
- Apply strong communication, problem‑solving, and stakeholder‑management skills to collaborate effectively across teams.
Requirements
- 3–4 years of experience as a Data Scientist
- Strong expertise in Python, R, SQL, and modern data‑science frameworks
- Hands‑on experience with TensorFlow, Keras, Scikit‑learn, and advanced deep‑learning frameworks
- Skilled in AWS or Azure cloud platforms, with at least one AWS certification preferred
- Proficient in statistical modelling techniques including regression, classification, clustering, and time‑series analysis
- Knowledgeable in building diagnostic, predictive, prescriptive, and autonomous AI systems
- Strong communication and stakeholder‑engagement skills
- Able to work collaboratively, manage complex challenges, and contribute to continuous improvement.
Benefits
- Opportunities to contribute to innovative, insight‑driven decision systems used across the organisation
- A supportive environment that encourages continuous learning and experimentation
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
Tech skills
Location requirements
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