Data Scientist

We are looking for an experienced Senior Data Scientist to join a Model Development Team in a leading financial organization.

The team drives strategic, organization-wide AI and Machine Learning initiatives across multiple business domains, including marketing, customer service, pricing, and technology.

The role involves developing end-to-end Machine Learning solutions, leveraging advanced AI technologies, and transforming complex data into actionable business insights.

Key Responsibilities

• Design, develop, and deploy Machine Learning models in an AWS-based environment.
• Lead end-to-end model development, from data exploration and feature engineering to model deployment and evaluation.
• Develop predictive models for classification, regression, and other business applications.
• Analyze large-scale structured and unstructured datasets from multiple data sources.
• Translate complex business challenges into innovative algorithmic and analytical solutions.
• Generate actionable insights using advanced analytics and AI technologies.
• Evaluate, monitor, and optimize model performance and effectiveness.
• Present analytical findings and strategic recommendations to business and technical stakeholders.
• Collaborate with cross-functional teams to deliver impactful, data-driven solutions.

Requirements – Must Have

• At least 5 years of hands-on experience in end-to-end Machine Learning model development, including proven experience with Classification and Regression models.
• At least 5 years of experience processing and analyzing large-scale tabular datasets.
• Proven hands-on experience developing with Python.
• Strong analytical thinking and advanced problem-solving skills.
• Ability to translate complex business requirements into effective technological and analytical solutions.
• Bachelor's degree in Mathematics, Statistics, Computer Science, Data Science, or another relevant quantitative field.

Nice to Have

• Experience developing applications based on Generative AI (GenAI).
• Experience working in large-scale, complex enterprise environments.
• Experience in the banking or financial services industry, including strong business domain understanding.
• Hands-on experience with cloud environments, particularly AWS.
• Experience processing large-scale datasets using PySpark.