Responsibilities:
• Partner with stakeholders to translate complex business requirements into Machine Learning problem statements.
• Work with cross-functional teams to ensure data availability, quality, and accessibility.
• Design, build, and deploy scalable Machine Learning and Deep Learning models, particularly for heavily imbalanced datasets.
• Collaborate with the MLOps team to develop robust data pipelines and ensure seamless model integration.
• Present findings and insights to senior stakeholders in a clear, business-friendly manner.
• Mentor and guide junior analysts, helping cultivate a strong data-driven culture within the team.
Skills:
• 5 - 10 years of experience in data science and machine learning.
• Highly proficient in SQL for data preparation and manipulation.
• Highly proficient in Python and in developing and deploying Machine Learning and Deep Learning models.
• Ability to interpret model outputs and translate data into actionable business strategies.
• Excellent communication and interpersonal skills to work across functions and present to diverse stakeholders.
• Bachelor's or Master's degree in Computer Science, Statistics, Mathematics, or a related quantitative field.
• Nice to Have Skills:
• Experience in using Pyspark for implementing and deploying the models.
• Experience in payments domain and fraud modeling using feedzai.
• Exposure to MLOps and model deployment in a production environment using AWS with experience in S3, Sagemaker, Feature Store, Cloudwatch, Event bridge, Athena.
• Experience working with Gitlab