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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates advanced proficiency in Python and SQL for developing and deploying machine learning and deep learning models in production environments. Expertise in MLOps practices and tools, with a strong focus on financial market data and data governance.
Highest-signal resume keywords
Python ProgrammingSQL ProficiencyMachine Learning DevelopmentAWS SageMakerMLOps Practices
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Machine LearningDeep LearningStatistical ModelsLLM-Based SolutionsData Preparation
Tools & Technologies
SageMakerDatabricksMLflowLangfuseAmazon Bedrock
Industry Keywords
Financial Market DataLakehouse ArchitectureData GovernanceAI Agents
Tech Stack
Tools & technologiesAWSCloudPythonSQL
About the role
Key responsibilities & impact- Work with financial market data.
- Develop and operate machine learning, deep learning, and statistical models from development through production deployment.
- Build and scale LLM-based solutions.
- Train, deploy, and monitor production models using SageMaker and Databricks.
- Track experiments and evaluate models and LLM-based solutions using MLflow and Langfuse.
- Work with the refined layer of the lakehouse, preparing the data that feeds the models.
- Ensure the quality and reliability of the data used to train and operate the models.
Requirements
What you’ll need- Advanced proficiency in Python and SQL.
- Experience developing machine learning, deep learning, and statistical models.
- Experience with AWS cloud services, including training and deploying models in SageMaker.
- Experience with Databricks and lakehouse architecture.
- Experience with LLMs in production environments, using Amazon Bedrock or equivalent platforms.
- Experience with MLOps practices and tools such as MLflow, Langfuse, or equivalent solutions.
- Preferred: strong knowledge of financial markets.
- Preferred: experience with AI agents.
- Preferred: knowledge of data governance and cataloging.
Benefits
Comp & perks- Ongoing professional development
- Dynamic and collaborative work environment
- Opportunity to work in a hybrid model