Specialist: Data Scientist - Fraud Strategy

South Africa·Johannesburgmid

Data ScientistData

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Requirements Summary

Scikit-learn, PyTorch, PyCaret, etc. Hadoop Big Data Platform: Spark, hdfs, hive, etc Python Tools: pytest, conda, poetry etc DevOps: Git (GitHub), bash, ssh, CI/CD Pipelines Cloud: DataBricks,

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Data ScientistData

With over 100 years of rich history and strongly positioned as a local bank with regional and international expertise, a career with our family offers the opportunity to be part of this exciting growth journey, to reset our future and shape our destiny as a proudly African group.

Job Summary

Empowering Africa’s tomorrow, together…one story at a time.
With over 100 years of rich history and strongly positioned as a local bank with regional and international expertise, a career with our family offers the opportunity to be part of this exciting growth journey, to reset our future and shape our destiny as a proudly African group.
My Career Development Portal: Wherever you are in your career, we are here for you. Design your future. Discover leading-edge guidance, tools and support to unlock your potential. You are Absa. You are possibility.

Job Summary
We are looking for a Data Scientist (AVP) to join the Personal and Private Banking Data Science team at Absa Bank. As a Data Scientist, you will become a collaborator within a team of specialist data scientists aiming to help Absa discover the insights hidden in its vast amounts of data and help enable smarter decisions to deliver better products and services and shape business strategy. You will be expected to take on the most complex artificial intelligence projects, as well as provide technical mentoring and coaching for junior team members.

Work with large-scale structured and unstructured datasets using modern data platforms (e.g. Databricks, AWS, other cloud-based environments).
Design, build, and deploy high-quality machine-learning models and applied AI solutions (including large language models) to drive strategic and competitive advantage, ensuring robustness, governance, and interpretability.
Partner with stakeholders across business, product, marketing, risk, strategy and technology teams to help translate their challenges into actionable data science models and embed insights into decision-making processes and strategy.
Partake in data science community of practice in the broader organisation by sharing knowledge and skills
Mentor junior data scientists and contribute to best practices in analytics, modelling, and storytelling.

Requirements

~1 min read

5+ years’ experience in data science or advanced analytics
Deep knowledge of machine learning methods, principles and frameworks
Strong programming and data querying skills (SQL, PySpark, Python)
Machine Learning: Scikit-learn, PyTorch, PyCaret, etc.
Hadoop Big Data Platform: Spark, hdfs, hive, etc
Python Tools: pytest, conda, poetry etc
DevOps: Git (GitHub), bash, ssh, CI/CD Pipelines
Cloud: DataBricks, AWS
Presentation skills: ability to efficiently present data and ML models insights to a non-technical audience
Team Skills: guiding junior team members, defining and maintaining team standards
Experience delivering end-to-end analytical solutions in a complex, data-rich environment (financial services experience is advantageous).

Bachelor’s degree in Statistics, Mathematics, Computer Science, Engineering, Data Science, Physics, or a related quantitative field.
Postgraduate qualification (Honours / Master’s) in Data Science is advantageous.
Bachelor's Degree: Information Technology/Mathematics/Statistics

Education

Bachelor`s Degrees and Advanced Diplomas: Business, Commerce and Management Studies (Required)

Absa Bank Limited is an equal opportunity, affirmative action employer. In compliance with the Employment Equity Act 55 of 1998, preference will be given to suitable candidates from designated groups whose appointments will contribute towards achievement of equitable demographic representation of our workforce profile and add to the diversity of the Bank.

Absa Bank Limited reserves the right not to make an appointment to the post as advertised