Job 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.
- Present and market proposed solutions to senior business and technology colleagues.
- Collaborate closely with business users to identify and execute machine learning opportunities.
- Work with the team and other technology partners on ML Ops aspects.
- Manage a global team of data scientists and data engineers.
Required Qualifications, Capabilities, and Skills:
- Bachelor’s Degree or equivalent experience in Computer Science or Data Science.
- 12+ years of experience as a data scientist.
- 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.
Preferred Qualifications, Capabilities, and Skills:
- Familiarity with Financial Services.
- Experience building ML models in a cloud environment.
- Experience with Big Data Platforms such as Hadoop.
- Outstanding written/verbal communication and presentation skills.
- Comfort with ambiguity and proven ability to structure problems.
- Team-oriented collaborator.