ML Engineer at Nedbank

Job Purpose

To design, prototype, and build next-generation analytic engines and services by applying strong expertise in Artificial Intelligence (AI)

Job Responsibilities

• Study and transform data science prototypes.
• Design machine learning systems.
• Research and implement appropriate ML algorithms and tools.
• Develop machine learning applications according to requirements.
• Select appropriate datasets and data representation methods.
• Run machine learning tests and experiments.

Essential Qualifications - NQF Level

• Matric / Grade 12 / National Senior Certificate
• Advanced Diplomas/National 1st Degrees

Preferred Qualification

• NQF Level 8
• Computer Science, Engineering, Econometrics, Mathematical Statistics, Actuary Science. Masters or Doctorate will be an added advantage.

Preferred Certifications

• Preferably any  Cloud (Azure, AWS), DEVOPS or Data engineering certification. Any Data Science certification will be an added advantage, Coursera, Udemy, SAS Data Scientist certification, Microsoft Data Scientist.

Minimum Experience Level

• 3-8 years’ experience in data science role
• Portfolio of delivering projects successfully into production
• ML Ops (Cloud Devops)
• ML Ops (ML engineering – running a Data Science platform)
• Deep knowledge of machine learning, statistics, optimization or related field
• Experience in Python(Must) and one additional language (SAS, Java Lua, Clojure, Scala, etc)
• Experience working with large data sets, simulation/ optimization and distributed computing tools (Kubernetes, Map/Reduce, Hadoop, Hive, Spark, etc.)
• Experience in end to end Use case delivery
• Ability to translate data narrative to business narrative

Technical / Professional Knowledge

• Analysing situations or data that requires an in depth evaluation of multiple factors
• Data Mining
• Data Warehousing
• Financial modelling and analytics
• Research and analytics
• Strategy planning and execution

Behavioural Competencies

• Decision Making
• Innovation
• Technical/Professional Knowledge and Skills
• Customer Focus
• Applied Learning
• Continuous Improvement