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Strong Tier-1 brand, generalist data scientist title, 3–6 years range, metro location and broad ML requirements.
Core ML/AI skills are transferable, but R2R finance domain requires domain knowledge.
Explicit 3–4+ year requirement plus mandatory ML, Python, deployment skills increases selectivity.
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Design, develop, deploy, and maintain AI/ML solutions to support Record to Report (R2R) finance processes, such as anomaly detection and predictive analytics.
Develop Python-based data pipelines and build/maintain ML models, LLM-powered tools, or AI agents to augment R2R productivity, ensuring scalability, explainability, and production readiness.
Collaborate with Enterprise AI, IT, and Data Platform teams for solution integration, deployment, security compliance, and ongoing enhancement.
Bachelor's degree in Computer Science, Data Science, Machine Learning, Statistics, Mathematics, or related field.
3+ years of data science or related work experience; Master's degrees may substitute for up to 1 year of experience.
Strong proficiency in Python and data science libraries with experience building, training, and deploying ML models or AI solutions.
Work Experience Required: 4–6+ years hands-on experience preferred (Minimum stated as 3+ years) in data science, analytics, or machine learning.
Technical operator with strong hands-on skills in Python and machine learning model development targeting finance process automation.
Experienced in end-to-end AI solution lifecycle including design, deployment, monitoring, and improvement, especially in R2R or finance automation contexts.
Comfortable collaborating cross-functionally with enterprise IT, AI, and data platform teams to ensure integration and adherence to security and architectural standards.