As a Financial Crime Analytics Lead, you will lead and manage multiple and competing stakeholder relationships, balance long and short-term project deliverables to ensure the successful delivery of project driven change activity in Financial Crime systems and processes.
Mandatory Skill(s)
- 7+ years of relevant professional experience in financial crime, sanctions, fraud, legal, risk management or finance area;
- 3 – 5 years of relevant Financial Crime Analytics experience one or more of the following areas:
Anti Money Laundering, Financial Crime, Transaction Monitoring, Customer KYC/CDD, Customer screening, etc. - Advanced skills in development, validation and monitoring of AML analytics models, strategies, visualizations;
- Understanding of evolving methodologies/ tools/ technologies in the Financial Crime management space;
- Experience in building models using AI/ML methodologies;
- Modeling: Experience in one or more of analytical tools such as Qlik, R, Python, SQL, etc.
- Knowledge of data processes, ETL and tools/ vendor products such as Fenergo, NICE Actimize, SAS AML, Quantexa, Ripjar, etc.
Desirable Skill(s)
- PMP (Project Management Professional) certification.
Responsibilities
- Take the lead to ensure systems and processes relating to customer risk models, coverage assessments and reports are well documented and maintained;
- Comply to Organization Frameworks, policies and any regulatory requirements;
- Collaborate with various departments (compliance, risk, legal, etc.) to gather input on the design, methodology, and assumptions used in customer risk models;
- Take ownership of documenting and presenting technical results to non-technical business audiences, including the formation and delivery of effective recommendations and solutions;
- Monitor and assess regulatory changes and advise the business on how these impact current risk models and financial crime detection processes;
- Apply thought leadership to enhance data analytics, including use of artificial intelligence and machine learning;
- Drive innovation by researching and implementing emerging technologies, such as artificial intelligence (AI) and machine learning (ML), to improve the accuracy, efficiency, and predictive capabilities of financial crime detection models;
- Work with data science and engineering teams to design and optimize automated systems for monitoring customer behavior, identifying suspicious activities, and refining the overall risk assessment process;
- Evaluate the effectiveness of AI/ML models in detecting financial crime and continuously enhance model performance by iterating on algorithms, refining data inputs, and ensuring their alignment with the organization's objectives and regulatory requirements.
If you are interested in this role, click on the “Apply to this job” button below or you could also write in with your CV to Meenakshi Saklani at meenakshi.saklani@sciente.com quoting the job title.
