ML / Data Analytics

This job is with WTW, an inclusive employer and a member of myGwork – the largest global platform for the LGBTQ+ business community. Please do not contact the recruiter directly.

Description

Summary :

We are seeking a talented Machine Learning Engineer to develop efficient, data-driven AI systems that enhance our predictive automation capabilities. The ideal candidate will be highly skilled in statistics and programming, with the ability to confidently assess, analyze, and organize large datasets. Additionally, the candidate should be proficient in executing tests and optimizing machine learning models and algorithms.

Role :

As a machine learning engineer, your primary responsibilities include :

Develop and implement data-driven ML predictive models to advance intelligent automation and reporting

Assess, analyze, and organize large datasets to extract meaningful insights

Execute tests to validate machine learning models and algorithms

Optimize machine learning models for improved performance and accuracy

Collaborate with cross-functional teams to integrate machine learning solutions into existing systems

Monitor and maintain machine learning models to ensure ongoing accuracy and efficiency

Research and stay updated on the latest advancements in machine learning and ML techniques and applications

Document processes, methodologies, and model performance for transparency and reproducibility

Troubleshoot and resolve issues related to machine learning model deployment and operation

Mentor and provide technical guidance to junior engineers, sharing best practices and fostering a culture of continuous learning

Qualifications

Requirements :

A bachelor's degree or master's degree in computer science, data science, or a related field

5+ years of experience in machine learning, data engineering, or software development

Strong programming skills and proficiency in languages commonly used for ML and related tasks

Big Data skills and be proficiency in data structures, modeling, and visualization

Proven background in statistical analysis and data analysis to support model training and evaluation

Excellent communication skills for working with stakeholders and translating technical concepts

Proficiency in Python and ML frameworks (TensorFlow, PyTorch, scikit-learn); experience with production-quality code

Strong background in statistics, mathematics, and data science

Experience with cloud platforms (AWS, GCP, Azure) and deploying ML models at scale is a plus

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