Sr. Quant Analytics Manager
Sr. Quant Analytics Manager
Job Number: 21-07122
Job Number: 21-07122
Be at the forefront on innovation. Eclaro is looking for a Sr. Quant Analytics Manager for our client in Cleveland, OH.
Eclaro’s client is one of the largest nonprofit healthcare plans in the United States that provides high-quality, affordable health care services and improve the health of the members and the communities the client serve. If you’re up to the challenge, then take a chance at this rewarding opportunity!
- Candidate is expected to partner and collaborate with Risk Modeling & Analytics (RM&A), Enterprise Security Services (ESS), and various other teams to ensure robust model design by making sure its structure, inputs, and parameters are sound and comprehensive from AML and OFAC perspective
- The candidate independently leads the review of the Model's overall suitability for its intended use and purpose, evaluation of the model's theoretical framework, and assessing data and assumptions used for model development
- The candidate is expected to communicate technical theories, observations, and models to a non-technical audience in a clear and concise manner
- The candidate in this role is expected to have advanced mathematics, data science, and business knowledge and is expected to act as a strategic advisor and creditable partner who works across teams for addressing business problems with innovative and effective solutions
- The candidate is responsible for guiding modeling practices, methods, and techniques as well as influencing data strategy with a focus on leveraging both current and emerging technologies for solving business problems
- Responsible for ensuring the overall effectiveness of the advanced Machine Learning (Client) models utilize for BSA/AML and OFAC surveillance
- Responsible for assessing BSA/AML and OFAC models for conceptual soundness; Assess model's overall suitability for its intended use and purpose, model's theoretical framework, data, and assumptions made during the development to ensure its relevance.
- Responsible for evaluating statistical and analytical approaches and testing used for model development, and benchmark methodologies. Evaluate ongoing tuning and calibration plans for ongoing model effectiveness testing. Assess and understand risks and contingency plans; when necessary perform independent statistical analysis, benchmarking, and other forms of testing.
- Responsible for identifying and gathering the relevant and quality data sources required to fully answer and address the problem; Provides strategic solutions through exploratory data analysis (EDA).
- Provides effective challenges in the design and implementation efforts to ensure the final model meets the regulatory expectations. Translates recommendations into communication materials to effectively present to mid-to-upper level management.
- Provide oversight in the development of tools and techniques for monitoring model performance and integrity post-production, and for identifying any quantitative or qualitative risk associated with the model.
- Responsible for creating and maintaining complete & clear documentation of the Modeling and Analytic activities, as well as the presentation of insights and recommendations to senior leadership
- Responsible for responding to inquiries from internal and external validators, auditors, and regulators. Responses include but are not limited to explaining models and solution processes clearly, as well as addressing any official findings and/or recommendations.
- Responsible for collaborating and partnering at all levels of the organization; guides, advises, challenges, and influences to drive organizational impact.
- Responsible for leveraging a vast amount of structured and unstructured data to extract actionable business insights
- Direct the data gathering, data processing, and data mining of large and complex datasets. Provide leadership in the development of algorithms using advanced mathematical and statistical techniques like machine learning to identify unusual behavior patterns
- Guide others on data modeling methods/techniques
- Ability to execute an analytics process from start to finish from problem specification through to a solution. Collaborate and partner with Model Developers, AML Risk Experts, Data Analysts, Architects, and Engineers for delivering data-driven solutions for the business
- Utilize predictive modeling and other advanced techniques for identifying innovative and effective solutions for detecting potential money laundering activities
- Master's degree (or its equivalent) in statistics, mathematics, economics, financial engineering, data sciences, predictive modeling, or other quantitative disciplines and at least 6 years minimum of relevant experience; or Bachelor's degree (or its equivalent) in statistics, mathematics, economics, financial engineering, data sciences, predictive modeling, or other quantitative disciplines and at least 7 years of relevant experience
- 5+ years of Applied Data Analysis, Model Development, Model Testing & Tuning experience
- Hands-on work experience with SQL or SAS, and Python or R for developing Machine Learning (Client) algorithms and solutions for solving real-world problems; Prior BSA/AML or OFAC modeling experience preferred
- 2+ years of experience in machine learning solution delivery in solving business problems
- Hands-on experience in the machine learning (Client) and Artificial Intelligence (AI) areas: Natural Language Processing (NLP), Deep Learning, Anomaly Detection, and Graph-based techniques
- Solid expertise using core statistical learning algorithms including linear models, decision tree, random forest, clustering/segmentation, dimension reduction, ensemble models, SVMs, and kernel methods to analyze large structured and unstructured datasets
- Mastery in programming and database language skills
- Knowledge of and ability to leverage traditional databases, cloud-based computing, and distribution computing
- Advance knowledge and experience in reporting & visualization Tools (e.g. Tableau, Qlikview, PowerBI, OBIEE), and Microsoft Office suite
- Knowledge of and ability to establish standards and best practices; forecast future modeling tools/techniques
- Identify, employ, and evangelize emerging techniques from industry/research
- Highly skilled at Influencing data and machine learning strategy
- Lead discussions about the pros/cons of its applications with senior leadership
- Lead work efforts from conception to delivery with minimal supervision
- Highly skilled at documentation and communication of analytics and modeling
- Translate technical observations to a non-technical audience
- Communicate observations to senior executives
- Knowledge of banking laws and regulations with emphasis on BSA, AML, and OFAC, risk identification and mitigation
- Knowledge of banking products and services
- Experience in handling 3rd party model reviews/challenges (e.g. Exams and Audits)
- Certified Anti-Money Laundering Specialist (CAMS) or willingness to pursue it
If interested, you may contact:
Elland Bondoc | LinkedIn
Equal Opportunity Employer: Eclaro values diversity and does not discriminate based on Race, Color, Religion, Sex, Sexual Orientation, Gender Identity, National Origin, Age, Genetic Information, Disability, Protected Veteran Status, or any other legally protected group status.