Manager, Quantitative Analytics

3 days ago

Johannesburg, Gauteng, South Africa Standard Bank of South Africa Limited Full time

Business Segment: Personal & Private Banking

Location: ZA, GP, Johannesburg, Baker Street 30

We are seeking a highly skilled Quantitative Analyst to join our team. In this role, you will leverage advanced statistical modeling and machine learning techniques to develop predictive models that drive business insights. You will also be responsible for designing and optimizing ETL (Extract, Transform, Load) processes to ensure data quality and accessibility for analytics.

Qualifications

Minimum Qualifications Required:

  • Bachelor's degree in Data Science, Statistics, Computer Science, Mathematics, or a related field.

Minimum Experience Required:

  • 3-5 years' experience.
  • Hands-on experience with statistical analysis, modeling techniques and machine learning.
  • Strong proficiency in SAS (advantageous), Python or R for data analysis and model development.
  • Strong SQL skills, including writing complex queries, working with relational databases, optimizing performance, and working with large datasets.
  • Experience designing, building, and maintaining ETL pipelines for structured and unstructured data.
  • Strong problem-solving skills with the ability to translate business needs into analytical solutions.
  • Ability to communicate insights effectively to both technical and non-technical stakeholders.

Beneficial Experience:

  • Experience in the Banking and/or Insurance industry.
  • Experience with machine learning frameworks (e.g., Scikit-learn, TensorFlow, PyTorch).

Additional Information

  • Analytical Thinking – Ability to break down complex problems, identify patterns, and derive meaningful insights from data.
  • Attention to Detail – Ensures accuracy in data analysis, modeling, and reporting.
  • Problem-Solving Skills – Thinks critically and develops innovative solutions to business challenges.
  • Communication Skills – Clearly presents complex quantitative insights to both technical and non-technical stakeholders.
  • Collaboration & Teamwork – Works effectively with cross-functional teams, including data engineers and business leaders.
  • Adaptability & Learning Agility – Stays updated with industry trends and emerging technologies.
  • Time Management & Prioritization – Manages multiple projects efficiently while meeting deadlines.
  • Proactive & Self-Motivated – Takes initiative in identifying opportunities for process improvement and optimization.
  • SQL & Database Management – Strong ability to write and optimize SQL queries, work with relational databases, and manage large datasets.
  • Predictive Modeling & Machine Learning – Experience with statistical techniques, regression models, decision trees, clustering, and other machine learning models.
  • ETL & Data Pipeline Development – Building, automating, and maintaining efficient ETL workflows.
  • Programming (SAS, Python, R) – Proficiency in data manipulation, modeling, and automation.
  • Statistical Analysis & Hypothesis Testing – Strong foundation in probability, statistical distributions, hypothesis testing, and A/B testing.
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