Onsite Lead GenAI Data Scientist - FinTech & MLOps

E-Solutions; Washington (District of Columbia); Sur place; USD 140 000 - 190 000; Plein temps

Résumé du poste

E-Solutions in Washington, DC is seeking a Lead Data Scientist to architect, build, and deploy advanced ML and AI solutions powering payments, fraud detection, risk decisioning, and financial data enrichment. The role requires hands-on GenAI, NLP, and foundation models expertise, with a focus on enterprise-scale deployment and responsible AI practices.

You will collaborate with engineering on cloud pipelines (Azure, AWS) and data platforms (Databricks, Snowflake) to transform complex financial

Qualifications

• Hands-on expertise in Generative AI lifecycle.
• Strong NLP and Deep Learning acumen.
• Experience architecting enterprise-scale ML/AI solutions.
• Proven ability to deploy models in cloud pipelines.

Responsabilités

• Fine-tune or adapt open-source and proprietary models.
• Design, build, and optimize Generative AI, LLM, and foundation models for enterprise fintech applications.
• Build high-performance models for NLP, document intelligence, anomaly detection, risk scoring, predictive analytics, and decisioning use cases.
• Lead experimentation to evaluate model accuracy, scalability, and fairness.
• Partner with engineering teams to deploy models on cloud-based ML pipelines (Azure, AWS) & data platforms (Databricks & Snowflake).
• Work with large-scale structured and unstructured datasets across the payments and financial ecosystem.
• Implement model monitoring, drift detection, and continuous retraining strategies.
• Evaluate and operationalize new AI technologies, foundation model architectures, responsible AI frameworks, and emerging research.

Connaissances

GenAI concepts

LLMs

NLP

Foundation models

MLOps

Fine-tuning

Outils

Azure

AWS

Databricks

Snowflake

Description du poste

E-Solutions in Washington, DC is seeking a Lead Data Scientist to architect, build, and deploy advanced ML and AI solutions powering payments, fraud detection, risk decisioning, and financial data enrichment. The role requires hands-on GenAI, NLP, and foundation models expertise, with a focus on enterprise-scale deployment and responsible AI practices.

You will collaborate with engineering on cloud pipelines (Azure, AWS) and data platforms (Databricks, Snowflake) to transform complex financial