oracle
Sr.Analyst-Data Science
American Express
Bengaluru, IND
Full-time
Senior · 2–3 years experience
Hybrid
Discovered 1 weeks ago
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Key Skills for This Role
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Qualifications
- Graduate or postgraduate degree in Statistics, Mathematics, Economics, Engineering, Management, Computer Science, or a related quantitative discipline from a recognized institution.
- 2–3 years of relevant experience in data science, advanced analytics, machine learning, or predictive modeling.
- Strong programming skills in Python and PySpark, with hands-on experience in data manipulation, statistical analysis, and machine learning model development.
- Solid understanding of machine learning and deep learning techniques, with exposure to Graph Neural Networks, graph-based algorithms, Transformer architectures, or related advanced AI methodologies.
- Familiarity with deep learning frameworks such as PyTorch or TensorFlow and cloud computing environments such as Google Cloud Platform.
- Experience working with large-scale datasets, feature engineering, data preprocessing, and model evaluation techniques.
- Strong problem-solving skills, analytical rigor, and the ability to translate complex business requirements into effective technical solutions.
- Excellent written and verbal communication skills, with the ability to present analytical insights and recommendations to diverse stakeholders.
- Demonstrated ability to exercise sound judgment, work collaboratively, and deliver high-quality analytical solutions in a dynamic business environment.
- Shift Timings: Mon - Wed 1:00 PM -9:30 PM; Thurs 11:00 AM- 7:30 PM; Friday - 8:30 AM -5 PM
Responsibilities
- Develop and enhance advanced machine learning and AI-driven solutions to identify emerging compromise patterns, detect suspicious behaviors, and strengthen risk decisioning capabilities.
- Apply cutting-edge techniques, including Graph Neural Networks (GNNs), graph-based learning, Transformers, Deep Learning, and other advanced ML algorithms, to solve complex business problems.
- Analyze large-scale, complex, and interconnected datasets to uncover hidden relationships, identify emerging risk signals, and generate actionable business insights.
- Design, develop, and optimize end-to-end analytical and modeling pipelines, including data preprocessing, feature engineering, model training, validation, and performance monitoring.
- Leverage Python, PySpark, and cloud-based platforms such as Google Cloud to build scalable, efficient, and robust analytical solutions.
- Explore and experiment with emerging AI/ML methodologies to continuously improve model effectiveness, predictive accuracy, and operational efficiency.
- Collaborate with cross-functional stakeholders to translate business challenges into innovative, data-driven solutions that deliver measurable business impact.
- Communicate complex analytical findings, model performance, and strategic recommendations effectively to both technical and non-technical audiences.
- Demonstrate strong analytical judgment, intellectual curiosity, and a proactive approach to identifying opportunities and solving complex business challenges. • Conduct extensive case reviews to generate insights for improving the model performance and decision-making processes • Collaborate with relevant stakeholders to ensure alignment of analytical and modeling efforts with business objectives, effectively managing stakeholder expectations and communication throughout the project lifecycle • Bring in ideas by incorporating external perspectives through reading research papers and identify appropriate use cases to enhance model development and innovation.
- Demonstrate strong analytical judgment, intellectual curiosity, and a proactive approach to identifying opportunities and solving complex business challenges.
- Conduct extensive case reviews to generate insights for improving the model performance and decision-making processes
- Collaborate with relevant stakeholders to ensure alignment of analytical and modeling efforts with business objectives, effectively managing stakeholder expectations and communication throughout the project lifecycle
- Bring in ideas by incorporating external perspectives through reading research papers and identify appropriate use cases to enhance model development and innovation.
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