Principal Data Scientist - Machine Learning

Placements24

Durban

On-site

ZAR 1,800,000 - 3,200,000

Full time

6 days ago
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Benefits offered by this job

Competitive salary
Health & retirement benefits
Learning budget and conference access
Career growth opportunities

Job summary

Placements24 in Durban seeks a Principal Data Scientist to lead advanced ML initiatives, architect models, and drive strategic insights across the organization.

You will mentor senior and junior data scientists, collaborate with engineering and product teams, deploy models to production, and champion best practices in data science and ML engineering.

Qualifications

  • Ph.D. or Master’s degree in a quantitative field.
  • 10+ years of data science experience with ML development and deployment.
  • Expertise in statistical modeling and ML algorithms (deep learning, gradient boosting, SVMs).
  • Proficiency in Python or R; experience with ML libraries (TensorFlow, PyTorch, scikit-learn).
  • Experience with big data (Spark, Hadoop) and cloud platforms (AWS/Azure/GCP).
  • Proven ability to lead projects and mentor team members.

Responsibilities

  • Design, develop, and implement scalable ML models for prediction, classification, and recommendations.
  • Lead end-to-end data science projects from data exploration to deployment and monitoring.
  • Mentor and guide a team of data scientists and analysts, fostering growth.
  • Collaborate with software engineers to productionize ML models and applications.
  • Identify opportunities to leverage data science to drive business value.

Skills

Team leadership
Mentoring juniors
Stakeholder communication
Project leadership
Problem solving

Education

PhD or Master’s in quantitative field

Tools

Python
R
TensorFlow
PyTorch
scikit-learn
Spark
Hadoop
AWS/Azure/GCP

Job description

About the Role

Our client is seeking a highly experienced Principal Data Scientist to lead their advanced Machine Learning initiatives in Durban. This senior role involves architecting and deploying sophisticated ML models that solve complex business problems, drive product innovation, and provide strategic insights across the organization. You will mentor junior data scientists, collaborate with engineering and product teams, and champion best practices in data science and ML engineering. This is a critical leadership position within a growing data-driven company, offering the chance to work on challenging projects that have a tangible impact on business outcomes in a beautiful coastal city.

Key Responsibilities
  • Design, develop, and implement scalable and robust machine learning models for prediction, classification, and recommendation systems.
  • Lead end-to-end data science projects, from data exploration and feature engineering to model deployment and monitoring.
  • Mentor and guide a team of data scientists and analysts, fostering technical growth and best practices.
  • Collaborate closely with software engineers to integrate ML models into production systems and applications.
  • Identify new opportunities for leveraging data science and ML to drive business value and innovation.
  • Communicate complex findings and model behaviors to technical and non-technical stakeholders.
Requirements
  • Ph.D. or Master's degree in Computer Science, Statistics, Mathematics, or a related quantitative field.
  • 10+ years of professional experience in data science, with a strong focus on machine learning development and deployment.
  • Expertise in statistical modeling, predictive analytics, and various ML algorithms (e.g., deep learning, gradient boosting, SVMs).
  • Proficiency in Python or R, and experience with ML libraries (e.g., TensorFlow, PyTorch, scikit-learn).
  • Experience with big data technologies (e.g., Spark, Hadoop) and cloud platforms (AWS, Azure, GCP).
  • Proven ability to lead projects and mentor team members effectively.
Benefits
  • Exceptional salary package with significant annual bonuses and stock options.
  • Comprehensive health, retirement, and insurance benefits.
  • Generous budget for continuous learning, attending conferences, and professional development.
  • Access to cutting-edge technology and large-scale datasets in Durban .
  • A culture that encourages innovation, collaboration, and career advancement.
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