Conformance Testing Team Lead

Job Title

Perform sophisticated analytics (including data profiling, statistical and predictive analytics, and risk analytics) to provide actionable insights that improve business outcomes, enhance data quality, and minimize risk. Provide consultation and thought leadership to business leaders and stakeholders on how to leverage analytics insights, manage data risk, and build strategies around analytics. Lead, guide, and educate junior data scientists and analysts to enable personal and professional growth and ensure successful delivery of complex, enterprise-scale analytics initiatives.

Essential Duties And Responsibilities

Following is a summary of the essential functions for this job. Other duties may be performed, both major and minor, which are not mentioned below. Specific activities may change from time to time.

1. Perform sophisticated data analytics, including data profiling, data quality assessment, data mining, statistical analysis, and predictive analytics, on structured and unstructured data across multiple platforms. Identify actionable insights from single or multiple data sources that measurably improve business outcomes and/or reduce business and data risk.

2. Take accountability and ownership of end-to-end testing environment solutions, including data sourcing, profiling, model design, technical development, validation, deployment, and measurement of business impact.

3. Design, develop, and maintain analytical solutions and automation to support data analysis, risk assessment, monitoring, and reporting.

4. Provide analytical consulting, risk-focused insights, and thought leadership to various business areas, fostering strong and strategic relationships with business, technology, risk, and compliance partners.

5. Co-design optimal solutions to complex business and risk problems by leveraging advanced analytics, data science techniques, and modern data platforms to create measurable business value.

6. Work effectively with diverse data environments and technologies, including relational databases (RDBMS), Flat files, integrating these sources into SAS-based analytics solutions

7. Maintain SAS programs, and SAS automation (e.g., SAS Base, SAS SQL, SAS macros, SAS Enterprise Guide, SAS Viya), while leveraging Python where appropriate for advanced analytics, integration, or automation use cases. Manage engagement across multiple analytics initiatives, lead and mentor junior teammates, and partner with cross-functional teams to ensure timely, high-quality delivery of analytics and risk solutions.

8. Exercise sound judgment and foster a strong risk management and data governance culture throughout solution design, development, and deployment. Partner with cross-functional teams to define and adhere to standards related to data usage, data quality, data governance, and analytics controls.

9. Actively learn, adopt, and promote new analytical tools, techniques, and platforms, continuously advancing in-house analytics capabilities toward industry-leading benchmarks. A

10. Actively mentor and guide junior teammates to create an inclusive, collaborative, and high-performing environment that empowers teammates to learn, grow, and build meaningful careers.

11. Drive overall team standards and take a leading role in hiring, onboarding, and ongoing coaching of new teammates.

Required Qualifications:

The requirements listed below are representative of the knowledge, skill and/or ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.

1. Bachelor's degree in a quantitative field such as Finance, Mathematics, Analytics, Data Science, Computer Science, or Engineering, or equivalent education and related training

2. Six years of related experience

3. Demonstrate domain expertise (SME) in one or more areas relevant to banking, financial services, fintech, quantitative risk management, and/or financial regulation; this will be demonstrated by several years of career progression in roles of increasing responsibility

4. In-depth knowledge in practices, theories and methodologies associated with the professional discipline such as statistics, programming (such as Python, R, SAS, etc.), machine learning, model development, business information visualization, etc.

5. Working knowledge of Hadoop, Pig, Hive, and/or NoSQL, Spark

6. Experience in managing multiple projects with tight deadlines and/or leading teams

Preferred Qualifications

1. Master's degree or PhD in a quantitative field such as Finance, Mathematics, Analytics, Data Science, Computer Science, or Engineering

2. Ten (10) or more years of relevant work experience if the candidate lacks a graduate degree

3. Strong hands-on experience with Python for analytics and data engineering 4. Prior experience in the banking, fintech, or other highly regulated industries is preferred

Other Job Requirements / Working Conditions

Sitting Constantly (More than 50% of the time) Visual / Audio / Speaking Able to access and interpret client information received from the computer and able to hear and speak with individuals in person and on the phone. Manual Dexterity / Keyboarding Able to work standard office equipment, including PC keyboard and mouse, copy/fax machines, and printers. Availability Able to work all hours scheduled, including overtime as directed by manager/supervisor and required by business need. Travel Minimal and up to 10%