Data Scientist Vice President (AFC Modelling, Analyst)

Deutsche Bank; North Carolina; On-site; USD 180,000 - 240,000; Full time

Job summary

Deutsche Bank in the United States (North Carolina) seeks a Vice President to advance data science within the Financial Crime AFC group. You will lead the development of ML solutions, partner with business, compliance, and technology teams, and shape analytical strategies.

Strong Python proficiency and experience with big data tools are required. You will drive predictive modeling, governance, and mentorship while ensuring ethical use of AI outputs in a regulated environment.

Qualifications

• Strong programming in Python with data science libraries.
• Experience with large-scale datasets, SQL, data modeling, and analytics platforms.
• Proven track record deploying ML or advanced analytics in regulated industries.
• Bachelor’s degree in CS, Data Science, Statistics, Mathematics, Engineering, or related field; Master’s preferred.
• Excellent communication and stakeholder management across levels.

Responsibilities

• Lead development and implementation of advanced analytics and ML solutions for Financial Crime and AFC initiatives.
• Drive data science strategy by partnering with business, compliance, technology, and risk stakeholders.
• Design, enhance, and monitor predictive models and analytical frameworks using large datasets.
• Conduct deep-dive analyses to identify risks, data quality issues, and improvement opportunities.
• Develop reporting, dashboards, and performance metrics to measure model effectiveness.
• Provide technical leadership, model governance support, and mentorship to junior members.

Skills

Python

Pandas

NumPy

Scikit-learn

SQL

Data modeling

Big data

Spark

Cloud platforms

Communication

Stakeholder management

Education

Bachelor's degree in a quantitative discipline

Master's degree preferred

Tools

Hadoop

Hive

Spark

Job description

• As a Vice President within AFC, you will play a key role in shaping and advancing data science and analytical capabilities across the Financial Crime organization. You will leverage advanced analytics, machine learning, and large-scale data platforms to develop innovative solutions that enhance risk detection, improve operational effectiveness, and support strategic decision-making
• Lead the development and implementation of advanced analytics and machine learning solutions supporting Financial Crime and AFC initiatives
• Drive data science strategy by partnering with business, compliance, technology, and risk stakeholders to solve complex problems and deliver actionable insights
• Design, enhance, and monitor predictive models and analytical frameworks using large and complex datasets
• Conduct deep-dive analyses to identify emerging risks, data quality issues, and opportunities to improve detection and operational effectiveness
• Develop reporting, dashboards, and performance metrics to measure model effectiveness and support strategic decision-making
• Provide technical leadership, model governance support, and mentorship to junior team members while promoting analytical best practices

Strong programming expertise in Python and data science libraries including Pandas, NumPy, and Scikit-learnAdvanced experience working with large-scale datasets, SQL, data modeling, and modern analytics platformsProven ability to leverage AI tools to enhance productivity, optimize workflows to solve business problems, while applying critical judgment to ensure responsible and ethical use of data and AI outputsSignificant experience developing and deploying machine learning, statistical, or advanced analytics solutions within financial services or other regulated industriesBachelor’s degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, Information Systems, or a related quantitative discipline; Master’s degree preferredStrong communication and stakeholder management skills with the ability to influence business and technical audiences at all levelsExperience within Financial Crime, Anti-Money Laundering (AML), Fraud, Compliance, Risk Management, or Regulatory Technology environmentsExposure to Transaction Monitoring, customer risk analytics, sanctions screening, or other financial crime surveillance programsExperience with Hadoop, Hive, Spark, cloud-based analytics platforms, or other big data technologiesStrong analytical and problem-solving skills with the ability to translate business challenges into scalable solutionsAbility to balance strategic thinking with hands-on execution in a fast-paced and evolving environment