Offer summary

Qualifications:

Strong problem-solving and coding skills, with a focus beyond basic programming., Experience in building machine learning models, particularly with Random Forest and Gradient Boosting., Proficiency in Python for data analysis and dashboard creation using libraries like Dash and Streamlit., 1-2 years of relevant experience, preferably with a background in engineering or data science, and healthcare experience is advantageous..

Key responsabilities:

Develop and implement machine learning models to address complex business challenges.

Enhance model performance using algorithms like Random Forest and AutoML.

Conduct detailed data analysis and feature engineering to improve model accuracy.

Communicate insights and recommendations to stakeholders and create interactive dashboards.

Job description

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.