Remote Machine Learning Engineer

Description:

• The Client is the world's first Performance Branding company, partnering with major brands to drive business growth through innovative marketing strategies.
• Their integrated operating model merges traditional marketing silos, allowing for alignment of marketing strategies with core business objectives.
• The role offers the opportunity to work with iconic brands such as The North Face, Timberland, Movado Watches, and Jose Cuervo.
• The company fosters a collaborative environment with small, versatile teams that are fast and adaptive to problem-solving and system building.
• The Machine Learning Engineer will lead the development and fine-tuning of predictive ML models, focusing on Ad Score and Ad Account Health.
• Responsibilities include ML model development, data analysis, feature engineering, model evaluation, deployment and integration, collaboration with cross-functional teams, and research and innovation.

Requirements:

• A Master's or Ph.D. in a related field with a strong academic background is required.
• Proven experience as a Data Scientist with a track record of developing and deploying predictive ML models is essential.
• Expertise in machine learning techniques, including regression, classification, clustering, and deep learning is necessary.
• Proficiency in data manipulation, feature engineering, and model evaluation is required.
• Strong programming skills in languages such as Python and experience with libraries like TensorFlow, PyTorch, or scikit-learn are mandatory.
• Excellent communication skills and the ability to collaborate effectively with cross-functional teams are essential.
• A passion for continuous learning and staying updated with the latest trends and technologies in data science is expected.
• Strong problem-solving abilities and the capacity to translate complex data into actionable insights are required.

Benefits:

• The position offers the opportunity to work with some of the biggest brands in the world, enhancing professional experience and exposure.
• Employees are part of a collaborative and innovative work environment that encourages growth and challenges.
• The role allows for continuous learning and staying updated with the latest developments in data science and machine learning.
• The company promotes a culture of acting as a trusted business partner, prioritizing the needs of partners above their own.