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charlotte,north carolina28245
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charlotte, north carolina

Job Description

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Job Title: Sr. Quantitative Analyst/Data Scientist. Location: Charlotte, NC - 28255 Contract: 12 Months of Contract

Summary:

Responsible for independently conducting quantitative analytics and complex modeling projects. Leads efforts in development of new models, analytic processes, or system approaches. Creates documentation for all activities and may work with technology staff in design of any system to run models developed. Incumbents possess excellent quantitative/analytic skills and can influence strategic direction, as well as develop tactical plans.

Job Description

Conduct an independent assessment by developing models or building an analytical framework to test AML screening model and other functions of AML high risk detection operations. Primary responsibility is to tune parameters or partner with model developers to re estimate model(s) to minimize the false negatives and identify triggers for false-positive Screening alerts to improve accuracy of model inputs, assumptions, methodologies, and model outcomes. Assess the model risk management framework of the organization, and controls related to model development, validation, implementation, and ongoing monitoring. Effectively manage the ongoing monitoring of the AML screening model by setting performance metrics, acceptable thresholds. Provide insights to the model owner and key stakeholders on the model performance. Engage with model risk management and LOB partners to identify causes when the metrics are in breach. Assist in on-boarding new applications / Clients into the Screening platform requiring detailed discussions with various lines of businesses in understanding the nature and type of data received from and assist in data mapping into standard data layout acceptable for Sanctions screening. Manage the multiple on-going initiatives from various projects, understand the Screening needs from the cross-LOB projects, provide model or analytical requirements to the projects and track the status of the model development or any analytical support needed for the projects. Collaborate with cross-LOB teams to integrate data science solutions into existing AML systems. Work with technology teams for requirements / testing and implementing changes to improve / automate processes and stay abreast of industry trends and emerging technologies. Communicate work through formal audit templates, reports, as well as through presentations to stakeholders and leaders. Work effectively as a team member with other quantitative analysts or data scientists within the organization or at the company.

Required Skills

Master's or bachelor's degree in finance, Economics, Mathematics, Statistics or related quantitative field. 5+ years' experience in the development, validation, use, and/or auditing AML Models Screening, economic sanctions, transaction monitoring, or fraud detection models. Awareness of AI / Machine learning concepts and ability to implement such strategies Excellent analytic, technical, communication and auditing skills. Strong understanding of quantitative modelling concepts, financial instruments, and risk assessment methodologies. Good experience in Data Analytics and interpretation of large volumes of Data. Programming experience with any language like Python, Spark, R, SAS, SQL and related tools such as SQL Server, Toad, PyCharm, Jupyter Notebook, Hue, Beeline. Experience with MS Suite and any presentation and visualization tools. Experience with Horizon for project management and code control tools such GIT and bitbucket.

Desired Skills and Experience:

Advanced degrees in a quantitative field. Knowledge of Screening programs requirements Ability to work with teams spread globally, under pressure, meet deadlines and navigate change. Ability to work and interact with people from a diverse range of backgrounds and opinions. Experience in Global Banking & Markets business process is a plus Experience in screening applications like Fircosoft. Certified Anti-Money Laundering Specialist (CAMS)

#INDIT

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