Build world-class AI/ML solutions for finance processes and drive significant business impact by tackling diverse challenges across multiple technologies and applications.
Requirements
Experience with machine learning techniques and advanced analytics (e.g., regression, classification, clustering, time series, econometrics, causal inference, mathematical optimization, NLP).
Experience with LLM and Gen AI.
Experience with Agentic workflows.
Proficiency in ML languages such as Python, SQL, Scala.
Experience with statistical techniques - i.e., data mining, data transformations, text mining, data visualization.
Experience building ML models in a cloud environment.
Experience with Big Data Platforms such as Hadoop.
Responsibilities
Build and train production-grade ML models on large-scale datasets to solve business use cases.
Utilize large-scale data processing frameworks to extract value from structured and unstructured data.
Apply Deep Learning models like NLP, LLM, and Gen AI for summarization, forecasting, and anomaly detection.
Conduct data modeling experiments, evaluate against baselines, and extract key statistical insights.
Create data models using best practices to ensure high data quality and reduced redundancy.
Stay current on industry trends and adopt the latest methodologies into existing implementations.
Work with the team and other technology partners on ML Ops aspects.
Other
Manage a global team of data scientists and data engineers.
Present and market proposed solutions to senior business and technology colleagues.
Collaborate closely with business users to identify and execute machine learning opportunities.
Bachelor’s Degree or equivalent experience in Computer Science or Data Science.
