Data Scientist - Hq Sandton

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Job title : Data Scientist - HQ Sandton
Job Location : Gauteng, Johannesburg

Deadline : December 13, 2024

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The Data Scientist role as such is responsible for: Model Development & Optimization Design, build, and optimize machine learning models, statistical techniques, and business logic to solve high-impact problems. Collaborate closely with Data Analysts to conduct rigorous testing, monitor model health, and implement enhancements based on performance insights. Work in tandem with Data Engineers to facilitate seamless implementation and deployment, coordinating timelines and technical requirements.
Technical Collaboration & Backlog Prioritization Align with Product Owners (POs) on backlog management, model prioritization, and task sequencing to maintain focus on high-impact projects. Effectively translate complex technical tasks into organized development routines and timelines, ensuring that the PO and other stakeholders have a clear understanding of model progress and expectations. Act as a technical partner in discussions with Data Engineers, contributing to conversations on data architecture and engineering needs.
Documentation & Stakeholder Communication Document all model developments, feature updates, and optimizations, providing comprehensive technical details. Support the PO in translating technical documentation for commercial teams, ensuring alignment and clarity on algorithm functionality and commercial implications.
Business Insight & Strategy Alignment Apply strong business acumen to ensure models address relevant business questions and drive impactful insights. Maintain awareness of business challenges, continuously refining models to meet changing business demands and enhance strategic value. Stay current with industry trends and emerging methodologies, continuously integrating best practices to enhance model relevance and effectiveness.
Minimum Requirements: Degree in Mathematics, Statistics, Data Science, or a related field with a strong foundation in calculus, linear algebra, probability, and statistics. Proficiency in SQL, Python, and PySpark, with extensive programming knowledge. Expertise in machine learning techniques, statistical modeling, classical optimization, and search algorithms. Strong knowledge of data engineering concepts and data architecture, important for facilitating technical conversations with engineering counterparts. Very strong problem-solving skills with an ability to manage complexity and ambiguity. Proven track record managing all aspects of a successful product throughout its lifecycle. Knowledge and experience with the application of CRISP-DM and Agile methodologies. Ability to translate complex technical tasks into organized routines and timelines; Must be able to translate backlog and timelines through Product Manager to ensure commercial teams have clear understanding of expectations for algo development & implementation. An extensive data science background is critical, and experience in sales/operations roles is a plus, but not required.

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