Machine Learning Engineer

Company:
Location: Rosebank, Gauteng

*** Mention DataYoshi when applying ***

Overview

    Job ID:

    54335

    Job Sector:

    Insurance

    Country:

    South Africa

    Region/State/Province/District:

    Gauteng

    Location:

    Rosebank

Job Details

Insurance

Job Purpose

Contribute to initiatives that drive improved customer experience and client insights through productionilizing machine learning models and building of production-ready and robust ML and AI systems, platforms and services, in many cases collaborating with software engineering teams.

Key Responsibilities/Accountabilities

Practical / Technical Knowledge • Strong foundational skills in mathematics and statistics • Strong understanding of Machine Learning Concepts • Strong Software Engineering Discipline (e.g. Source Control, CI/CD) • Experience with major ML frameworks (Tensorflow, PyTorch, scikit-learn) • Experience with building and tuning Deep Learning models • Experience with Big Data Processing Libraries (e.g. Spark, Dask) • Experience working with structured and unstructured data • Experience building end-to-end solutions on Cloud (SalesForce, AWS, Azure) • Experience working with and tuning services in Cloud Analytical Modelling and Solutioning

• Modelling: Required to apply the most appropriate algorithms and/or build novel algorithms / techniques to fit the problem statement. Must take advantage of data science capabilities offered by different cloud/on prem vendors where appropriate to increase project velocity, take advantage of latest start-of-the-art commercialized data science solutions and reduce internal technical debt. • Solutioning: Required to incorporate ML models into software that meets the upstream of downstream system requirements. (i.e., Engineering Batch, Streaming or API based ML pipelines) • Technical Documentation: Required to deliver technical artefacts articulating the architecture and model robustness of Cloud solutions

Project – Mapping Implementation

• Project Pipelining: Ability to work with technical stakeholders to identify new ML/API/Cloud initiatives. Ability to perform rapid EDA / prototyping exercises to help size projects and high-level success criteria • Business Problem Statement Crystallization Required to convert conceptual Insurance DS needs (non-technical) into crystalized problem statements that can be scientifically measured • Academic and Commercial Research: Required to review academic and commercial literature to identify similar models / solutions that can solve for the business problem statement • Data Analysis and Engineering: Ability to apply engineering and math skills to analyze and prepare structured / unstructured data for modelling

Planning and Organizing Skills

• Able to operate independently on projects • Able to create and size high level plans for projects • Able to create and size tasks in alignment with Sprint plans / goals • Able to work on 2-3 concurrent initiatives at a time where needed • Able to run ML projects and manage direct and virtual resources Stakeholder management

• Ability to work with technical stakeholders to identify new ML/API/Cloud initiativesAttends regular stakeholder meetings. • Ensures alignment with key technical stakeholders such as business unit managers. • Actively engages with stakeholders to fulfil and deliver the Information Management objectives.

Preferred Qualification and Experience

Type of qualification: First Degree Field of study: IT and Computer Sciences

Type of qualification: First Degree Field of study: Mathematical Sciences

certifications or professional memberships Proficiency in coding for structured and unstructured Query languages e.g. SQL, Python, R, JSON, C#, Java, C++. Ability to create APIs.


Type of qualification: Honours Degree Field of study: IT and Computer Sciences

Type of qualification: Masters Degree Field of study: IT and Computer Sciences

Information Technology, Actuarial Science, Statistics, Mathematics, Data Science, or related field


Knowledge/Technical Skills/Expertise

Job Family: Data Science and Machine Learning Engineering
Years: 5-7 Years
Experience Description:
  • Strong foundational skills in mathematics and statistics
  • Strong understanding of Machine Learning Concepts
  • Strong Software Engineering Discipline (e.g. Source Control, CI/CD)
  • Experience with major ML/AI frameworks (Tensorflow, PyTorch, scikit-learn)
  • Experience with building and tuning Deep Learning models
  • Experience with Big Data Processing Libraries (e.g. Spark, Dask)
  • Experience working with structured and unstructured data
  • Experience building end-to-end solutions on Cloud (SalesForce, AWS, Azure)
  • Experience working with and tuning services in Cloud

PLEASE NOTE: All our recruitment and selection processes comply with applicable local laws and regulations. We will never ask for money or any form of payment as part of our recruitment process. If you experience this, please contact our Fraudline on +27 800222050 or forward to TransactionFraudOpsSA@standardbank.co.za

*** Mention DataYoshi when applying ***

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