Lead Data Scientist, Current

• The ideal candidate will possess a strong background in statistical analysis, machine learning techniques, programming (), and preferably a deep understanding of VertexAI’s capabilities along with experience in deploying and scaling models using Google Dataflow
• 7+ years of experience in data science or machine learning roles, with expertise in developing and deploying machine learning models
• Degree in Computer Science, Statistics, Mathematics, or related field
• Proficiency in Python programming and machine learning libraries (e.g., TensorFlow, scikit-learn) for model development and deployment
• Experience with data preprocessing, feature engineering, and model selection techniques to optimize performance
• Familiarity with Google Cloud Platform services, particularly VertexAI and Dataflow, for scalable data processing and model training
• Proficiency in Scala programming language for developing scalable and efficient machine learning solutions is preferred
• Strong understanding of statistical analysis, hypothesis testing, and experiment design
• Excellent problem-solving skills with the ability to translate business requirements into technical solutions
• Strong communication and collaboration skills with the ability to work effectively in a fast-paced, cross-functional environment

Desirable

• We are in search of an experienced Lead Data Scientist
• In this role, you will lead the design, development, and deployment of machine learning models and algorithms, leveraging VertexAI to solve complex business challenges in the fintech domain
• Analyze diverse datasets to extract meaningful insights and patterns, identifying actionable opportunities for optimization and innovation
• Design, develop, and deploy predictive, clustering, recommendation system and anomaly detection models and algorithms ( Preferably using VertexAI) for various applications, including customer segmentation, fraud detection, credit risk assessment, and personalized recommendations
• Conduct exploratory data analysis, feature engineering, and model selection to optimize performance and enhance predictive accuracy
• Implement and maintain scalable machine learning pipelines and workflows on Google Cloud Platform, ensuring reliability, scalability, and efficiency
• Leverage Google Dataflow for processing large-scale data and building scalable data processing pipelines
• Evaluate model performance using appropriate metrics and techniques, conducting A/B testing and iterating on models to continuously improve accuracy and business impact
• Collaborate with engineering teams to integrate machine learning models into production systems, monitor performance, and troubleshoot issues
• Contribute to the development of best practices, standards, and documentation for machine learning processes and methodologies