Senior Data Science Engineer designing and optimizing transaction monitoring models for financial crimes at Fidelity. Collaborating with data scientists and compliance professionals in the analysis and detection of suspicious activities.
Responsibilities
Collaborate with team members and compliance partners to understand AML typologies and red flags we must detect
Assist in building detection models and features using SQL, Python, DBT (Data Build Tool), and Snowflake
Develop and maintain data pipelines that integrate multiple data sources (e.g., Snowflake, Oracle, MongoDB, Postgres)
Support the implementation of machine learning and AI techniques to enhance suspicious activity detection by analyzing and identifying appropriate target data
Contribute to testing frameworks for unit, regression, and model performance validation
Help monitor and tune model performance to ensure compliance and effectiveness
Participate in code reviews and knowledge sharing to maintain best practices
Explore emerging technologies and assess their applicability to financial crime detection
Requirements
Bachelor’s degree in Computer Science or equivalent technical expertise
2+ years of experience in software or data engineering
Advanced proficiency in SQL and Python
Strong analytical mindset, curious and self-sufficient in exploring and understanding data across systems
Prior experience working with machine learning algorithms, AI agents, and large language models (LLMs) is advantageous
Exposure to customer and transactional data, particularly in fraud or AML contexts, is advantageous
Experience working with dbt (data build tool) is a plus
Benefits
comprehensive health care coverage and emotional well-being support
market-leading retirement
generous paid time off and parental leave
charitable giving employee match program
educational assistance including student loan repayment, tuition reimbursement, and learning resources
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