Data Scientist
Rep is the first AI-powered Concierge (sales chatbot) for eCommerce. It proactively approaches disengaged site visitors and offers shopping assistance for everyone. As a result, Rep sells more products and handles up to 90% of all support requests. We’re looking for a Data Scientist to design, develop, and deploy cutting-edge machine learning models that drive our AI-powered solutions. This role requires a blend of deep technical expertise, business acumen, and problem-solving skills to optimize our AI capabilities and enhance user experiences. Responsibilities - Design, develop, and test Machine Learning models using SageMaker and Python , covering the full model lifecycle from data collection, robust ETL processes, model selection, validation, and deployment . - Implement, test, and optimize Machine Learning models in our product to improve performance and customer engagement. - Develop recommendation algorithms that enhance user experiences and drive business growth. - Work with big data technologies to extract, process, and analyze large datasets efficiently. - Ensure model fairness, mitigate bias, and enhance explainability in AI decision-making. - Optimize feature selection techniques and employ advanced target encoding methods. - Utilize machine learning techniques such as decision trees (XGBoost, Random Forest), logistic regression, anomaly detection , and other methodologies to refine model accuracy. - Collaborate with engineers, product managers, and business stakeholders to align ML solutions with company goals. - Conduct rigorous A/B testing and model performance evaluations. - Continuously research and implement state-of-the-art machine learning methodologies to enhance AI-driven solutions. Skills & Qualifications - At least 3 years of hands-on experience in machine learning, data science, or a related field. - Strong proficiency in Python and experience with ML frameworks like PyTorch, TensorFlow, or Scikit-learn. - Experience in deploying ML models in production environments, particularly using AWS SageMaker . - Deep understanding of machine learning methodologies , including anomaly detection, decision trees (XGBoost, Random Forest), feature selection, and bias mitigation . - Expertise in big data technologies and handling large-scale datasets efficiently. - Experience in ETL pipelines , data transformation, and engineering best practices. - Strong grasp of SQL and NoSQL databases. - Background in A/B testing and statistical analysis for model validation. - Ability to translate complex data problems into actionable business insights. - BSc/MSc/PhD in Computer Science, Engineering, Statistics, or a related field. - Being referred by a current Rep team member is a plus! If you’re excited about pushing the boundaries of AI-driven eCommerce and want to be part of an innovative team, we’d love to hear from you!