Senior Machine Learning Scientist (Enterprise Solution)
Appier is seeking a Senior Machine Learning Scientist to join its Enterprise Solution Science Team, focusing on applying advanced machine learning technologies to real-world marketing challenges by integrating omnichannel customer data. This role involves end-to-end development, from problem definition to deploying models into production, contributing to Appier's mission of turning AI into ROI by making software intelligent.
The Senior Machine Learning Scientist will work on topics such as user intention prediction, user segmentation, product recommendation, campaign content optimization, and send time optimization. Responsibilities include collaborating with product teams to translate business needs into well-defined machine learning problems, working closely with ML engineers to ensure reliable model deployment, conducting offline and online evaluations, and continuously optimizing models post-deployment. Staying updated with the latest research and mentoring junior scientists are also key aspects of the role.
Candidates should possess a Master's or PhD degree in Computer Science, Machine Learning, Mathematics, Electrical Engineering, or related fields, with over three years of experience applying machine learning techniques in areas such as prediction, optimization, segmentation, or recommendation. Proficiency in Python and ML frameworks like PyTorch or TensorFlow is required, along with practical experience in deploying enterprise-grade ML models, including developing model pipelines and performance dashboards. Strong analytical and problem-solving skills, a passion for new technologies, and experience in cross-functional collaboration and leading industry projects are essential.
Preferred qualifications include industry experience in the MarTech domain and a strong passion for building customer-centric products.
Appier offers a dynamic work environment with opportunities for professional growth, encouraging innovation and collaboration among its team members.