Senior Data Scientist - Assistant Vice President
About The Position
The Senior Data Scientist joins a global Data Science team supporting AI-driven transaction monitoring and analytics for Wealth Management. The role partners with U.S.-based product users and stakeholders to understand customer needs, product use, and opportunities for enhancement. It combines hands-on Data Science expertise with product thinking and stakeholder management to translate business problems into practical machine learning and AI solutions. Working with a global team, the Senior Data Scientist helps deliver measurable business value while advancing established machine learning and emerging generative AI capabilities. The role leads machine learning and AI use cases from requirements gathering and data identification through model development, testing, validation, deployment, and go-live. Employees hired into this role are expected to work in Deutsche Bank’s New York office according to its hybrid working model.
Requirements
- Bachelor’s degree in Data Science, Computer Science, Statistics, Mathematics, or a related quantitative discipline, or equivalent relevant experience.
- At least 5 years of experience in applied Data Science, machine learning, or advanced analytics, including hands-on development with Python and SQL using complex datasets.
- At least 3 years of experience developing machine learning models using statistical techniques and relevant Python machine learning libraries or frameworks.
- At least 3 years of experience translating business requirements and customer needs into technical requirements and practical Data Science, machine learning, or AI solutions.
- At least 3 years of experience developing, testing, deploying, or supporting machine learning solutions in a production or enterprise environment, including version control, testing, and deployment practices.
- Experience partnering directly with product users and business stakeholders to understand customer needs, evaluate product enhancement opportunities, and communicate technical concepts and analytical findings to nontechnical audiences.
- Ability to leverage AI tools to enhance productivity and optimize workflows while applying critical judgment to ensure responsible and ethical use of data and AI outputs.
Nice To Haves
- At least 2 years of experience with Google Cloud Platform (GCP), Microsoft Azure, or Amazon Web Services (AWS) supporting Data Science, machine learning, or analytical solutions.
- Experience developing or implementing generative AI (GenAI) or large language model (LLM) solutions for practical business use cases.
- Experience in Financial Services, Financial Crime, transaction monitoring, Wealth Management, or another regulated environment.
- Experience with model monitoring, data pipelines, MLOps, APIs, or related technologies used to deploy and operationalize machine learning solutions.
- A proactive, consultative approach to collaboration, innovation, knowledge sharing, and continuous learning.
Responsibilities
- Partner with U.S. product users and business stakeholders to understand customer needs, how analytical products are used, and opportunities for product enhancement.
- Translate business and customer needs into clear technical requirements and practical Data Science, machine learning, and AI solutions.
- Lead end-to-end implementation of machine learning and AI use cases, from requirements gathering and data identification through development, testing, validation, deployment, and go-live.
- Develop, improve, and support machine learning solutions for AI-driven transaction monitoring and Wealth Management analytics, and evaluate practical generative AI opportunities.
- Analyze complex business and customer activity data to identify trends, improve analytical outputs, and generate actionable insights.
- Collaborate with the global Data Science team and cross-functional partners to deliver solutions in response to evolving product, business, and regulatory needs.
Benefits
- Hybrid working model with in-office and work-from-home flexibility.
- Generous vacation, personal, and volunteer days.
- Employee Resource Groups that support an inclusive workplace and promote community engagement.
- Competitive compensation packages.
- Health and wellbeing benefits.
- Retirement savings plans.
- Parental leave and family building benefits.
- Educational resources.
- Matching gift and volunteer programs.
- Physical, emotional, and financial wellness benefits.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
