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Machine Learning Developer / Engineer (EST Hours) - Remote

Machine Learning Developer / Engineer (EST Hours) - Remote

ISTA Personnel SolutionsRizal, Cagayan, Philippines
15 hours ago
Job description

Overview

STA 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.

Working requirements

  • 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.

Required Skills

  • Strong problem-solving and coding skills, more than just a programmer.
  • Experience building machine learning models.

    • Ideally have experience

  • 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.

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