Intermediate Data-Scientist Job in Randburg
Job Description
Intermediate Data-Scientist Job. In the realm of data-driven decision-making and analytics, the Intermediate Data Scientist emerges as a pivotal figure, equipped with the skills and expertise to extract meaningful insights from vast datasets. With a blend of statistical analysis, machine learning techniques, and programming proficiency, the Intermediate Data Scientist navigates complex data landscapes to uncover patterns, trends, and correlations. Their role extends beyond mere data analysis, encompassing the ability to translate findings into actionable recommendations and strategic insights.
Responsibilities of Intermediate Data-Scientist Job
- Take all necessary actions to ensure compliance with relevant statutory, legislative, policy, and governance requirements in the area of accountability.
- Ensure implementation of relevant policies, governance, and practice standards across the business Maintain expert knowledge on relevant legislative amendments, industry best practices, and internal compliance procedures and requirements.
- Ensure compliance is adopted in terms of systems and procedures as laid out by the business.
- Innovate by finding the best-fit solution for the situation such as the flexibility of delivery and customized solutions which result in more efficient outcomes.
- Maintain ownership of models through regular audits and updates to ensure relevance.
- Plan and perform regular model updates that capture evolving business complexity in current models Challenge current models to ensure relevance and accuracy of outputs.
- Test outputs and accuracy of models to ensure relevance.
- Validate, interpret, and create reports and presentations for data analytics management and relevant stakeholders.
- Review and assist more junior Quantitative Analysts with processes and models.
- Adhere to model-building policies, standards, frameworks, and governance processes.
- Ensure own ethical usage of information that complies with restrictions applied for privacy and sensitivity classification.
Requirements
- Bachelor’s degree or higher in Computer Science, Statistics, Mathematics, Data Science, or a related field.
- Proven experience in data analysis, statistical modeling, and machine learning techniques.
- Proficiency in programming languages such as Python, R, or SQL for data manipulation and analysis.
- Strong understanding of statistical concepts and methodologies.
- Experience with data visualization tools such as Tableau, Matplotlib, or ggplot2.
- Familiarity with big data technologies and frameworks such as Hadoop, Spark, or TensorFlow.
- Ability to clean, preprocess, and wrangle large datasets for analysis.
- Excellent problem-solving skills and attention to detail.
- Effective communication skills to convey complex findings to non-technical stakeholders.
- Ability to work independently and collaboratively in cross-functional teams.
- Continuous learning mindset to stay updated on industry trends, tools, and techniques in data science.
