Maintain and enhance ingestion/enrichment pipelines for internal content (parsing/extraction, normalization, metadata enrichment, deduplication, and quality monitoring)

Implement and maintain access-aware retrieval by propagating/enforcing document permissions through indexing and query-time filters, including audit logs and validation tests

Improve source attribution so responses reliably point to the correct documents and sections in a consistent format.

Extend and harden tool/workflow execution and automations (scheduled/trigger-based), including retries, timeouts, idempotency, concurrency controls, and run history

Operate the platform in production: observability (logs/metrics/tracing), alerting, incident support, performance tuning, and cost controls, plus runbooks and handover documentation

8+ years of hands-on experience in Data Science and 2+ years in Machine Learning, with a proven track record, demonstrated through a robust portfolio of projects.

Strong programming skills in languages such as Python and familiarity building ETL pipelines.

Expertise in SQL and experience with both relational (preferably Postgres) and NoSQL databases

Solid experience with OpenSearch

Familiarity with AWS cloud platform and its services.

Experience with version control systems (e.g., Git) and CI/CD pipelines.

Ability to build scalable infrastructure to embed and search very large number of documents.

Ability to move fast in an environment where things are sometimes loosely defined and may have competing priorities or deadlines.

Expertise in ML

Strong English skills (B2 and higher)

Strong verbal and written communication skills.

Ability to work independently and collaborate in a group.

Agile certification

Oracle/Microsoft attestations and certifications

Domain knowledge

Trading and Capital Markets