Associate Lead - Data Science

Description

• Apply advanced statistical techniques and machine learning/deep learning algorithms to large datasets to develop models that optimize financial decision-making and operational efficiency.
• Analyze and interpret complex data from various sources (structured and unstructured) to identify trends, anomalies, and actionable insights.
• Build, train, and validate machine learning/deep learning models, ensuring their performance meets business needs.
• Continuously improve and optimize existing models by integrating new data sources and refining algorithms.
• Collaborate with cross-functional teams, including managers, engineers, and other data scientists, to define and prioritize data-driven solutions.
• Communicate insights and findings to stakeholders in a clear and concise manner through reports, visualizations, and presentations.
• Apply cutting-edge techniques such as Multi-agent systems (MAS), GenAI models to financial use cases.
• Stay updated with the latest developments in data science, AI, and financial technology.

• Bachelors or Master s degree in Data Science, Statistics, Computer Science, or a related field.
• 2+ years of hands-on experience in data science, preferably in financial services or fintech environments.
• Strong proficiency in Python and experience with machine learning frameworks (TensorFlow,PyTorch) and ML libraries.
• Knowledge of SQL and experience working with large-scale databases and data warehouses.
• Excellent analytical skills, with the ability to draw meaningful insights from complex data.
• Strong communication skills, with the ability to explain technical concepts to non-technical audiences.

• Familiarity with financial data and experience in the wealth management industry.
• Experience working in Amazon SageMaker and Bedrock.
• Knowledge of AWS AI/ML services and proficiency in PySpark.