ML Data Scientist - Predictive Analytics (Stellenbosch)

Placements24; Stellenbosch; Presencial; ZAR 700 000 - 1 100 000; Tempo integral

Vantagens oferecidas por esta oferta de emprego

Competitive salary

Professional development

Stellenbosch location

Cutting-edge projects

Resumo da oferta

Placements24 in Stellenbosch, South Africa, seeks an accomplished Data Scientist with a Machine Learning focus to join an office-based analytics team. You will develop predictive models, clean large datasets, and collaborate with stakeholders to translate business questions into data-driven solutions.

You should hold a Master's or PhD in a quantitative field, have 3+ years of experience, and be proficient in Python or R, with libraries such as scikit-learn, TensorFlow, PyTorch, or Keras.

Qualificações

• Master's or PhD in a quantitative field.
• 3+ years of professional data science experience with ML.
• Strong programming with Python or R and ML libraries.

Responsabilidades

• Develop and implement machine learning models for predictive analytics and other data science tasks.
• Clean, process, and transform large datasets from various sources.
• Evaluate model performance using appropriate metrics and statistical methods.
• Collaborate with business stakeholders to translate needs into data science problems.
• Communicate findings clearly to technical and non-technical audiences.

Conhecimentos

Python

R

Machine Learning

Spark

SQL

Formação académica

Master's degree in Computer Science

PhD in a quantitative field

Ferramentas

scikit-learn

TensorFlow

PyTorch

Keras

Pandas

NumPy

Descrição da oferta de emprego

Placements24 in Stellenbosch, South Africa, seeks an accomplished Data Scientist with a Machine Learning focus to join an office-based analytics team. You will develop predictive models, clean large datasets, and collaborate with stakeholders to translate business questions into data-driven solutions.

You should hold a Master's or PhD in a quantitative field, have 3+ years of experience, and be proficient in Python or R, with libraries such as scikit-learn, TensorFlow, PyTorch, or Keras.