ISTA Personnel Solutions South Africa - we are a global Business Process Outsourcing (BPO) company, partnering with a USA Client in the Healthcare Industry and are in search of a Machine Learning Developer / Engineer to join a rapidly expanding team, working remotely.
PLEASE NOTE THE FOLLOWING:
- Working Hours: This role requires you to work USA hours, Mon - Fri, from 8:30am to 5:30pm EST time (2:30pm to 11h30pm South African time. NOTE: These hours are subject to change depending on daylight savings and/or the operational requirements of the company.)
- Work Environment: This is a remote role for South African Citizens only.
- Internet Requirements: A fixed fibre line with a minimum speed of 25 Mbps (upload & download) and the ability to support a wired Ethernet connection is mandatory. Applicants without a fixed fibre line cannot be considered.
- Power Backup: A reliable power backup solution is required to manage load shedding and power outages. Applicants without a power backup cannot be considered.
Requirements
Required Skills:
- Strong problem-solving and coding skills, more than just a programmer
- Experience building machine learning models
Ideally have experience with:
- Random Forest, Gradient Boosting, AutoML
- Performing well on Kaggle machine learning competitions (advantageous)
- 1-2 years of relevant experience
- Python skills for data analysis and building dashboards with libraries like Dash, Streamlit, Panel, Bokeh
- Actuarial experience would be an advantage
Ideal Candidate Profile:
- Background as an engineer or data scientist, ideally with healthcare experience
- Able to discuss specific models built, methodologies used, and feature engineering approaches
Duties and responsibilities:
- Develop and implement machine learning models to solve complex business problems from the ground up.
- Use algorithms such as Random Forest, Gradient Boosting, and AutoML to enhance model performance
- Ensure models are scalable and maintainable
- Perform detailed data analysis to extract meaningful insights
- Conduct feature engineering to improve model accuracy
- Validate and clean data to ensure high-quality datasets for model training
- Communicate findings and recommendations to stakeholders in a clear and concise manner
- Collaborate with team members to integrate models into existing systems and workflows
- Create dashboards and visualizations using Python libraries such as Dash, Streamlit, Panel, and Bokeh
- Present data-driven insights through interactive and user-friendly dashboards
- Provide regular reports on model performance and business impact
- Apply machine learning techniques to healthcare-specific problems
If you are not contacted with 14 working days for this role, please consider your application unsuccessful.