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Michael Struwig is a seasoned software engineer with expertise in artificial intelligence, machine learning, and data science. He has a PhD in Electrical and Electronic Engineering from Stellenbosch University and has worked in various roles, including Head of Artificial Intelligence at OpenBB and Chief Executive Officer at Hudson & Thames Quantitative Research. He is proficient in languages such as English and Afrikaans and has experience with technologies like FastAPI, Kubernetes, and AWS.

Experience

    • Head of Artificial Intelligence
      • Nov 2023 - Present

  • Hudson & Thames Quantitative Research
    • Cape Town, Western Cape, South Africa
    • Chief Executive Officer
      • Mar 2023 - Oct 2023
      • Cape Town, Western Cape, South Africa

  • Primer
    • Cape Town, Western Cape, South Africa
    • Senior Backend Engineer
      • Oct 2022 - Mar 2023
      • Cape Town, Western Cape, South Africa

      Senior engineering role at a fast-growing start-up in the payment orchestration space that handles millions of payments across the world. Worked in multiple cross-functional teams, and was responsible for system design, payment processor integrations, customer profile persistance, and API design. Responsible for owning technical initiatives from initial concept through to deployment in a live production environment.Tech stack:- FastAPI- Kubernetes- AWS- PostgreSQL- Redis

    • South Africa
    • Software Development
    • 1 - 100 Employee
    • Technical Lead
      • Jan 2022 - Oct 2022

      Technical team lead and product development role for a Personalized Healthcare and Genetics product for a greenfield team.Responsibilities include project management, end-user engagement, architecture design, software engineering, code review and mentorship. Primary decision maker for high-impact technical decisions.Tech stack:- Python (Django, PyData stack)- Cloud (Microsoft Azure -- Blobstore, Serverless, Docker, Kubernetes, etc.)- DevOps CI/CD (git, Bitbucket, Pipelines, etc.)

    • Data Scientist
      • Mar 2018 - Jan 2022

      Responsibilities----------------- Handling and execution of "potential client" proof-of-concept projects- Machine learning workflow design and automation- Machine learning model design and iteration- Building infrastructure on cloud platforms- Warehousing and processing of large datasetsTechnical Skillset:----------------------------- Python (PyData stack + ML frameworks + NLP frameworks + Parallel processing frameworks )- Spark (via Databricks + standalone)- Cloud infrastructure (AWS + Azure stacks)- DevOps (Build automation, CI, etc)- Data visualization

    • Data Science Internship
      • Dec 2017 - Feb 2018

      Three month Data Scientist internship. Responsibilities included extensive data auditing, exploratory data analysis (EDA) as well as visualization of large datasets and accompanying analysis. Additional projects involved implementing templates for production-ready ML workflows and assisting in the implementation of cross-language support within a ML Python workflow and conducting a workshop to introduce clients to the new architecture.Notable skills developed:Production-ready PythonLarge dataset visualization (Datashader, Bokeh)Distributed data processing (Dask, Hive)

  • Praelexis
    • Stellenbosch, South Africa
    • Internship (Data Scientist)
      • Jul 2017 - Aug 2017
      • Stellenbosch, South Africa

      Six week Data Science internship program. Assigned to an internal team and tasked with producing work in Python across a variety of projects, requiring significant acquisition and development of Data Science skills. Additional responsibilities include attending planning meetings and contributing to team decisions.Projects:- Music generation using LSTM recurrent neural network.- Internal GPU feasability assessment and report. (related blog post: http://praelexis.com/2017/08/16/gpu-not-gpu/)- Exploratory data analysis and visualization of undisclosed dataset.Noteworthy skills include experience with modelling, training, evaluating and designing Neural Networks and other machine learning models using Keras, Lasagne and Scikit-learn frameworks (Python), as well as unit and integration test authoring and cloud computing experience across Amazon AWS, Microsoft Azure and FloydHub. Also includes additional development of data EDA and dataset visualization skillsets.

Education

  • 2018 - 2022
    Stellenbosch University
    Doctor of Philosophy - PhD, Electrical and Electronics Engineering
  • 2015 - 2017
    Stellenbosch University
    Master of Engineering - MEng (Upgraded to PhD), Electrical and Electronics Engineering
  • 2015 - 2015
    Università degli Studi di Trento
    (M.Eng) International Exchange Programme, Electrical and Electronics Engineering
  • 2011 - 2014
    Stellenbosch University
    Bachelor of Engineering - BE, Electrical and Electronics Engineering
  • 1998 - 2010
    Elkanah House
    High School, Graduated with Distinction

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Industry Focus. “Financial Services”

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