Data Scientist Specialist

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• Information Technology
• Application Development
• Manage Self Professional

Apply deep domain-specific expertise in machine learning, data mining, and information retrieval to architect and build highly specialized and advanced analytic engines and services, pushing the boundaries of knowledge in the field and providing expert guidance to the enterprise.

• Specialised in the development of best-in-class statistical models and algorithms, leveraging years of experience and expertise.
• Conduct advanced statistical analysis to uncover deep insights and patterns in complex datasets.
• Provide actionable insights and strategic advice to stakeholders, drawing from an extensive background in the field of AI/ML.
• Create significant value by harnessing the potential of enterprise-wide data and translating it into valuable business solutions.
• Apply comprehensive financial services domain knowledge to analyse datasets and develop statistical models and algorithms that cater to specific financial services use cases.
• Spearheaded the integration of AI/ML solutions into existing banking systems, optimizing processes, and driving operational efficiency while adhering to industry standards.
• Experienced in deploying or contributed to deployment of multiple end to end data science solutions that has yielded significant value in the organisation at an enterprise level.
• Implement cutting-edge AI and ML solutions, establishing robust system operations and maintenance structures under the purview of senior leadership.
• Play a key role in shaping the organization's AI/ML strategy, aligning it with current and future needs.
• Lead the transformation of data science prototypes into scalable machine learning solutions ready for production deployment.
• Design dynamic ML models and systems that possess the capability to adapt and retrain as necessary, guided by years of hands-on experience.
• Periodically assess the performance of ML systems, ensuring alignment with corporate and IT strategies.
• Demonstrate an end-to-end understanding of applications and machine learning algorithms, showcasing expertise at every step.
• Pioneering the use of machine learning algorithms and libraries, setting the standard for the enterprise.
• Oversee the software engineering and design aspects of projects, providing comprehensive end-to-end solutions.
• Extensive expertise in programming toolsets (such as Python, R, etc) for data preprocessing, advanced statistical analysis, machine learning, and developing complex data pipelines is required
• Produce end-to-end designs encompassing infrastructure, security, networks, and more, collaborating with other engineering leads to ensure a comprehensive data science solution.
• Effectively communicate complex processes to non-programming experts, utilizing years of experience to simplify understanding.
• Continuously research and implement best practices to enhance existing machine learning solutions, utilizing extensive domain knowledge.

• Advanced Machine Learning and AI Expertise: Demonstrated ability to develop, implement, and optimize complex machine learning models and AI algorithms.
• Strong Programming
  
  Skills:
  
  Proficiency in multiple programming languages such as Python, R, and SQL, with a deep understanding of data structures and algorithms.
• Experience with Big Data Technologies: Hands-on experience with big data tools Spark, or similar.
• Experience with Model Deployment: Proven experience in deploying machine learning models into production environments using tools like Docker, Kubernetes, or cloud services (AWS, Azure, GCP).
• Proficiency in MLOps
  :
  Knowledge of MLOps practices to streamline the deployment, monitoring, and maintenance of machine learning models.

• Matric / Grade 12 / National Senior Certificate
• Advanced Diplomas/National 1st Degrees

• A Master's or Ph.D. in Data Science, Computer Science, Statistics, or a related field.
• Certifications in Machine Learning, Data Analytics, or Big data Technologies are highly desirable.