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Srg Recruitment (Pty) Ltd

Senior Ml Engineer: Build Production Ml Pipelines

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Summary

Data Scientist specializing in machine learning, recruited by SRG for a client in Durban. Day to day: develop, train and deploy ML models for prediction, classification and clustering, engineer features from large datasets, and integrate models into production systems. Core stack: Python/R, scikit-learn, TensorFlow, PyTorch, Spark/Hadoop, SQL.

Data Scientist

Our client is seeking a talented and innovative Data Scientist specializing in Machine Learning to join their advanced analytics team in Durban . You will be responsible for developing and implementing sophisticated machine learning models to extract actionable insights from large, complex datasets. This role requires a deep understanding of statistical modeling, predictive analytics, and algorithm development. You will work closely with business stakeholders to identify opportunities, define problems, and deliver data-driven solutions that enhance product offerings and drive business growth. This is an exceptional opportunity to contribute to cutting-edge AI initiatives in a collaborative and research-oriented environment.

Key Responsibilities

  • Develop, train, and deploy machine learning models for predictive analytics, classification, and clustering.
  • Perform data exploration, cleaning, and feature engineering on diverse datasets.
  • Evaluate model performance, conduct A/B testing, and iterate on models for continuous improvement.
  • Translate complex analytical findings into clear, concise recommendations for business stakeholders.
  • Collaborate with data engineers and software developers to integrate ML models into production systems.
  • Stay abreast of the latest advancements in machine learning and artificial intelligence research.

Requirements

  • PhD or Master's degree in Data Science, Statistics, Computer Science, or a related quantitative field.
  • 5+ years of experience in applying machine learning techniques to solve real-world business problems.
  • Strong proficiency in Python or R, including libraries like scikit-learn, TensorFlow, and PyTorch.
  • Solid understanding of statistical concepts, experimental design, and data mining techniques.
  • Experience with big data technologies (e.g., Spark, Hadoop) and SQL is essential.
  • Excellent communication and presentation skills, with the ability to explain complex models to non-technical audiences.

Benefits

  • Competitive salary with comprehensive performance incentives.
  • Generous health insurance plan and wellness programs.
  • Support for continuous learning, including funding for courses and conferences.
  • Access to state-of-the-art computing resources and datasets.
  • Be part of a pioneering team shaping the future of data-driven decision-making.

Data Scientist - Machine Learning Specialist

Our client is seeking a talented and analytical Data Scientist with a specialization in Machine Learning to join their growing team in Durban . This role is instrumental in extracting actionable insights from complex datasets, developing predictive models, and driving data-driven decision-making across the organization. You will work with cutting-edge tools and techniques to solve challenging business problems, contributing significantly to product development and strategic planning. This is an excellent opportunity for a passionate data professional to innovate and apply advanced analytical methods in a supportive and technologically advanced environment.

Key Responsibilities

  • Design, develop, and deploy machine learning models to address key business challenges such as prediction, classification, and anomaly detection.
  • Perform exploratory data analysis, feature engineering, and data preprocessing to prepare datasets for modeling.
  • Collaborate with engineering and product teams to integrate ML models into production systems and applications.
  • Evaluate and optimize model performance, utilizing appropriate metrics and validation techniques.
  • Communicate complex findings and insights clearly to both technical and non-technical stakeholders through compelling visualizations and

Skills

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