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Data Scientist at Vodafone United States

Johannesburg, Gauteng, South Africa -

Full Time

Start Date

Immediate

Expiry Date

08 Apr, 26

Salary

0.0

Posted On

08 Jan, 26

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

GenAI, Large Language Models, Recommendation Systems, Data Manipulation, SQL, PySpark, NoSQL, Python, R, Java, Machine Learning, MLOps, Visualization Tools, Analytical Thinking, AI, Machine Learning Ecosystems, Real-time Decisioning

Industry

Telecommunications

Description

Experience in GenAI and Large Language Models (LLMs) is a plus. Hands-on experience in building and optimizing recommendation systems. Experience in data manipulation: use of structured data tools (e.g., SQL), and unstructured data platforms (e.g. PySpark, NoSQL) Proficiency in at least one relevant programming language: Python, R, Java Experience across major machine learning model frameworks (e.g. H2O, scikit-learn, PyTorch, Tensorflow) and techniques (e.g. random forest, gradient boosting, k-means segmentation, multiple regression, factor analysis, time-series forecasting) Exposure to cloud native deployment of models and working with containerized technologies such as Docker and Kurbernetees. Knowledge of MLOps and LLMOps concepts and deployment of models through batch and real-time architectures. Professional and/or academic experience in Big Data analytics & deployment of models and algorithms to solve real-world problems (with deep statistical and machine learning modelling expertise) Familiarity with visualization tools (e.g. Tableau, Qlik, D3, Apache Superset, Plotly, PowerBI, Opensearch, Grafana) Good interpersonal communication and presentation skills Ability to work in a fast-paced environment. Analytical and expansive thinking with a strong desire to deliver and develop. Design & Systems Thinking in relation to AI and Machine Learning Eco Systems. Real-time Decisioning & Intelligence use case deployment and evaluation experience.

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Responsibilities

The Data Scientist will build and optimize recommendation systems and manipulate both structured and unstructured data. They will also deploy models and algorithms to solve real-world problems using advanced statistical and machine learning techniques.