I am working with a consulting firm hiring Data Scientists at the Senior Associate and Manager levels within their financial crimes and analytics unit. This role involves developing and deploying machine learning models for anti-money laundering (AML) and financial crime prevention. Candidates should have strong proficiency in machine learning techniques, AI, and tools such as Python, R, SAS, SQL, Tableau, and Power BI for data visualization. AML experience is required for the Manager level.
Responsibilities:
- Lead key workstreams, staying updated on trends and contributing to team knowledge capital.
- Design, build, and deploy production-quality models using machine learning techniques (including neural networks, NLP, and predictive analytics) to solve complex business problems.
- Enhance custom models, including credit risk, fraud detection, and predictive analytics tools.
- Support the development and implementation of regulatory compliance solutions, particularly in financial crimes (AML, BSA, OFAC).
- Manage compliance-related consulting engagements, applying statistical methods, regression analysis, clustering, and machine learning models.
- Use robotic process automation (RPA) tools and AML systems; communicate results to clients, stakeholders, and leadership using visualization tools like Tableau and Power BI.
Qualifications:
- Bachelor's degree required; Master's preferred in fields such as Computer Science, Economics, or Operations Research.
- 3-5+ years of experience in data analytics, machine learning, or related fields.
- Proficiency in Python, R, SAS, SQL, and statistical methods.
- Expertise in machine learning techniques (e.g., regressions, clustering, Bayesian probabilities) and AI technologies (e.g., neural networks, NLP, predictive modeling).
- Experience in financial crimes consulting and regulatory environments (AML, BSA, OFAC).
- Strong communication and project management skills.
