A dynamic company focused on engineering smart solutions that give power and tech that integrates with all energy tariffs, so that drivers can charge at the cheapest and greenest times available seeks an Intermediate Data Scientist who will be accountable for designing, producing, analysing, documenting and enhancing a range of predictive models across the entire credit life cycle. Responsibilities: Analyse complex datasets to identify trends, patterns, and correlations relevant to business objectives. Develop predictive models and machine learning algorithms to forecast customer behaviour, optimise resource allocation, and improve operational efficiency. Collaborate with stakeholders to define key performance indicators (KPIs) and develop metrics for measuring the success of data science initiatives. Design and implement data visualisation tools and dashboards to communicate insights effectively to non-technical stakeholders. Stay current with emerging technologies and best practices in data science, machine learning, and artificial intelligence. Translate business requirements into technical solutions. Work closely with cross-functional teams to analyse large datasets and develop predictive models. Qualifications and Experience: Bachelor's or Master's degree in Computer Science, Statistics, Mathematics, or a related field. 5+ years of experience in data analysis, machine learning, and predictive modelling. Proficiency in programming languages such as Python, Java, or SQL. Experience working with large datasets and data manipulation tools (e.g., Pandas, NumPy) will be beneficial. Familiarity with cloud computing platforms (e.g., AWS, Azure, Google Cloud). Knowledge of big data technologies (e.g., Hadoop, Spark). Experience with data visualization tools (e.g., Tableau, Power BI, Grafana). The Reference Number for this position is NG59736 which is a Permanent Remote position offering a cost to company from R700k up to R900k per annum negotiable on experience and ability. Contact Nokuthula at nokuthulag@e-merge.co.za or call her on 011 463 3633 to discuss this and other opportunities. #J-18808-Ljbffr