Cape Town Lead Data Scientist - NLP & AI Innovator

Impact; Cape Town; On-site; ZAR 1,000,000 - 1,800,000; Full time

Benefits offered by this job

Annual bonus potential

Medical aid and retirement fund

Professional development budget for培训

Conferences & trainings

Cape Town office

Cutting-edge technology access

Job summary

Impact is seeking an experienced Lead Data Scientist in Cape Town to spearhead advanced analytics, lead a team of data scientists and engineers, and drive the development of sophisticated machine learning models and AI-powered solutions.

You will translate complex data into strategic recommendations for stakeholders, ensure production-ready data pipelines, and stay at the forefront of AI research and responsible data practices.

Qualifications

• PhD or Master’s in Data Science, CS, or related field.
• 7+ years of data science experience with leadership.
• Expertise in statistical modelling, ML, DL, and AI techniques.
• Proficiency in Python or R with relevant libraries (Scikit-learn, TensorFlow, PyTorch).
• Strong experience with SQL and big data technologies (Spark, Hadoop).
• Excellent leadership, communication, and stakeholder management skills.

Responsibilities

• Lead and mentor a team of data scientists and engineers.
• Develop, implement, and validate advanced ML models and predictive algorithms.
• Conduct in-depth data analysis, feature engineering, and EDA on large datasets.
• Collaborate with engineering teams to deploy analytics in production.

Skills

Leadership

Communication

Stakeholder management

Mentoring

Education

Master's or PhD in Data Science/CS/Computational Linguistics

Tools

Python

R

Scikit-learn

TensorFlow

PyTorch

Spark

Hadoop

Job description

Impact is seeking an experienced Lead Data Scientist in Cape Town to spearhead advanced analytics, lead a team of data scientists and engineers, and drive the development of sophisticated machine learning models and AI-powered solutions.

You will translate complex data into strategic recommendations for stakeholders, ensure production-ready data pipelines, and stay at the forefront of AI research and responsible data practices.