Hybrid AML Data Scientist & Modeler

Deutsche Bank; New York (NY); Hybrid; USD 90,000 - 253,000; Full time

Benefits offered by this job

Hybrid work model

Health benefits

Retirement plans

Parental leave

Job summary

Deutsche Bank is seeking a Data Scientist (Analyst - Vice President) in New York, NY, to drive the AML transaction monitoring data strategy and develop platform reporting for model performance. You will interpret data quality issues, work with business units to define model specs, and address findings in a timely manner.

The role requires strong Python in technical stack, experience in data science/model development, and familiarity with financial crimes space.

Qualifications

• Bachelor's or Master's degree in Computer Science, Data Science, MIS, Information Management, or equivalent.
• Proven experience in data science or model development in a business setting.
• Strong Python programming skills (Scikit-learn, Pandas, NumPy).
• Experience in Financial Crimes space and knowledge of AML/Transaction Monitoring desirable.

Responsibilities

• Drive and execute AML Transaction Monitoring Americas data strategy aligned with Global Data Strategy.
• Develop and evolve platform reporting statistics to monitor model performance.
• Conduct deep dives to identify data quality issues and track remediation to resolution.
• Collaborate with 1LOD to understand products and define TM model specifications/flags.
• Review open AML TM findings and address them promptly.

Skills

Python

Scikit-learn

Pandas

Numpy

Data science

Model development

SQL

Hadoop

HiveQL

Data visualization

AML knowledge

Relational DBs

Education

Bachelor/Master in CS/DS/MIS

Tools

SQL

Hadoop

Hive

Data viz tools

Job description

Deutsche Bank is seeking a Data Scientist (Analyst - Vice President) in New York, NY, to drive the AML transaction monitoring data strategy and develop platform reporting for model performance. You will interpret data quality issues, work with business units to define model specs, and address findings in a timely manner.

The role requires strong Python in technical stack, experience in data science/model development, and familiarity with financial crimes space.