Senior Data Science Engineer - Financial Crimes
About The Position
Financial Crimes Models & Analytics is seeking a Senior Data Science Engineer to contribute to the design, development, and optimization of our transaction monitoring surveillance models. You will work closely with our Data Scientists, Business Intelligence analysts, Investigators, and Compliance professionals to translate regulatory requirements into scalable, rules based & machine learning detection models. This role requires a blend of data engineering, analytics, and AI/ML expertise , along with an understanding of financial crime risks associated with Fidelity's cryptocurrency and brokerage offerings . If you’re passionate about data analysis, feature engineering, and machine learning to help fight financial crime, this is an excellent opportunity to grow your career! Financial Crimes Models & Analytics is made up of Data Scientists, Data Engineers, Business Intelligence, and Data Visualization analysts. Our team has broad responsibility for Fidelity Investments transaction monitoring across multiple business units, including Brokerage and Digital Assets. We leverage data to detect potential suspicious activity, customer behavior changes, and more. Coverage areas include insider trading, high risk money movement, customer behavior & potentially suspicious transactional patterns, elder financial exploitation, low-priced securities, emerging risks, cryptocurrency transactions and many more.
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 , with the ability to deliver meaningful business analytics and insights.
- Strong analytical mindset, curious and self-sufficient in exploring and understanding data across systems.
Nice To Haves
- 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.
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
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 to develop your career
Stand Out From the Crowd
Upload your resume and get instant feedback on how well it matches this job.
What This Job Offers
Job Type
Full-time
Career Level
Mid Level
Number of Employees
5,001-10,000 employees
