Senior Data Remediation Specialist (US)

Work Location:

Mount Laurel, New Jersey, United States of America

Hours:

40

Pay Details:

$72,280 - $117,520 USD

TD is committed to providing fair and equitable compensation opportunities to all colleagues. Growth opportunities and skill development are defining features of the colleague experience at TD. Our compensation policies and practices have been designed to allow colleagues to progress through the salary range over time as they progress in their role. The base pay actually offered may vary based upon the candidate's skills and experience, job-related knowledge, geographic location, and other specific business and organizational needs.

As a candidate, you are encouraged to ask compensation related questions and have an open dialogue with your recruiter who can provide you more specific details for this role.

Line of Business:

Data & Analytics Job Description:

We are looking for a skilled data remediation analyst to ensure our ongoing compliance with FDIC Part 370, which governs recordkeeping for timely deposit insurance determination. In this position, the analyst will be responsible for conducting in-depth data remediation analysis, performing research and quality assurance on several account and customer data concerns each day, as well as identifying exception populations. Additionally, they will develop and maintain recurring reports that highlight data issues requiring remediation. The successful candidate will bring expertise in data analysis and reporting, a solid understanding of banking products, and familiarity with regulatory requirements. Strong cross-functional collaboration skills are essential, as is the ability to enhance the completeness, accuracy, traceability, and overall usability of deposit account records. These efforts are critical for robust FDIC 370 reporting, ongoing testing, and ensuring certification readiness.

Depth & Scope:

• •Conduct data remediation analysis for deposit account data elements required for FDIC Part 370 compliance, including account holder identifiers, beneficial owner information, grantor and beneficiary data, ownership right and capacity classifications, pending reason codes, and required output file fields.
• •Experience with data remediation within financial institutions is highly preferred.
• •A thorough understanding of both lending and deposit accounts will further enhance a candidate’s suitability for this position.
• •Candidates should be adept at understanding relational data sets to pinpoint specific scenarios, with a keen eye for accuracy and detail.
• •Outstanding organizational skills and effective time management are vital for success in this role.
• •The candidate should demonstrate expertise in Excel.
• •While SQL experience is not required, it would be considered a valuable asset.
• •The candidate will operate within a collaborative team environment, maintaining a clear understanding of team objectives while independently managing and executing assigned responsibilities with a high degree of accountability and professionalism.
• •Expert level professional role, considered subject matter expert with in-depth knowledge / expertise in own domain / field of specialty and working knowledge of broader related areas
• •Requires expert level conceptual and practical knowledge for own area of specialty and knowledge of broader related areas
• •Advanced analytical and problem solving skills and fluent in one or two programming language
• •Works autonomously on a range of tasks and may be relied upon to coach / educate others
• •Lead projects of moderately to complex risk and resource requirements; may lead end-to-end processes or functional programs
• •In-depth experience working with very large datasets and familiarity with big data technologies
• •Keeps abreast of rapid business and technology innovation within business information management field
• •Familiar with visualization tools
• •Analyzes, designs, develops data repositories, warehouses and marts, data movement, data wrangling, data mapping and transformation (ETL) processes
• •Supports solutions, applications, platforms, and/or tools that are leveraged across all functional groups (e.g., Data Scientists, Business Insights & Analytics, etc.)
• •May also be responsible for developing sophisticated data preparation frameworks and architecture to create or modify data features for consumption by Data Scientists
• •Supports data modeling capabilities in order to structure business data to be consumed / translated into a variety of novel capacities
• •Supports business teams in the use and understanding of the data and reporting solutions
• •Develops data road map/information management strategies and corresponding technical solutions on integrating, transforming, and/or managing data
• •Drives data-centric solution development focusing on complex data integration
• •Adopts the Enterprise Data model in alignment with direction from the OCDO and other data & analytics functional groups
• •Solicits, analyzes, and understands data requirements (i.e., using market research, requirements gathering, feature planning, user experience / design considerations, etc.) to enable development of information management solutions

Education & Experience:

• •Undergraduate degree or Technical Certificate
• •5+ years of relevant experience from a business administration, statistical, mathematical, scientific or financial background
• •Proficient knowledge of various data sources, tools and technologies used in preparing summaries and reports
• •Analytical and problem solving skills are required to interpret data and draw conclusions
• •Knowledge of current and emerging competitor and market trends
• •Skill in using analytical software tools, data analysis methods and reporting techniques
• •Skill in mentoring/coaching others
• •Skill in using computer applications including MS Office
• •Ability to communicate effectively in both oral and written form
• •Ability to work collaboratively and build relationships
• •Ability to work successfully as a member of a team and independently
• •Ability to exercise sound judgement in making decisions
• •Ability to analyze, organize and prioritize work while meeting multiple deadlines
• •Ability to handle confidential information with discretion

Customer Accountabilities:

• •Analyzes and understands business and data requirements to develop complete business solutions, including data models (entity relationship diagrams, dimensional data models) and business rules, data life-cycle management, governance, lineage, metadata and reporting elements.
• •Applies automation and innovation on data platforms and on-going on any new development projects / initiatives aligned to business or organizational strategies
• •Designs and implements complex business data information management frameworks to provide a solution that meets business requirements
• •Collaborates with technology and business partners to resolve issues and ensure requirements and established SLAs
• •Works closely with various technology/project teams to understand business data and provide analysis and requirements to ensure the data design / development initiatives are in line with the planned design and standards

Shareholder Accountabilities:

• •Works with other various partners/ stakeholders to ensure project success
• •Develops business requirements by researching / analyzing and documenting business data requirements
• •Provides expert guidance within projects and other various change initiatives to support data impact assessments and data risk mitigation
• •Implements processes aligned to data information management standards and ensure data quality (e.g., rules / thresholds / assessments, etc.) and requirements are developed
• •Develops and maintains knowledge of data available from upstream sources and data within various platforms
• •Identifies critical data / critical data elements to support Business Segment data governance and/or data management frameworks / programs
• •May be