Machine Learning Developer / Engineer (EST Hours) - Remote

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 9:00am to 6:00pm EST time (15:30pm to midnight 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 fully remote working role.
• 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.