Data Quality Analyst

Mindlance; Charlotte (NC); Hybrid; USD 90,000 - 130,000; Full time

Job summary

Mindlance is seeking an Analytics Consultant to own model and data quality for AML initiatives in Charlotte, NC (Hybrid). The 12+ month engagement focuses on proactive data-quality checks, data profiling, and governance to ensure reliable model inputs and auditable processes.

You will collaborate with cross-functional teams to identify defects, analyze root causes, and implement preventive controls, enabling timely, data-driven decisions.

Qualifications

• Proficient in SQL for Teradata environments.
• Profile datasets to understand data characteristics, quality issues, anomalies, and potential problems.
• Identify data defects or quality issues affecting AML datasets.
• Document controls and audit readiness in governed environments.
• Coordinate data issues with multiple stakeholders across technology, data, and business teams.

Responsibilities

• Perform proactive data-quality checks to identify issues before AML model input.
• Profile datasets to understand data characteristics, quality issues, and anomalies.
• Identify, track and remediate data defects impacting AML datasets.
• Ensure data going into AML models meets quality standards.
• Develop preventive monitoring to catch issues earlier in the data lifecycle.

Skills

SQL

Data analysis

Data profiling

Data quality

Root cause analysis

Stakeholder collaboration

Model governance

Data validation

Project management

Change management

Tools

Teradata

Job description

Job Title: Analytics Consultant - Model and Data Ownership

Location: Charlotte, NC - Hybrid

Duration: 12 months+ (Possibility of Extension/Conversion)

Job Description:

• Proactive data-quality checks: Establish checks that identify problematic data before it enters or impacts AML models.
• Data profiling: Profile datasets to understand data characteristics, quality issues, anomalies, and potential problems.
• Data issue / defect identification: Detect data defects or quality issues affecting the datasets used by AML models.
• Data issue management and resolution: Track, investigate, and help remediate identified data-quality issues rather than simply reporting them.
• Model-input quality assurance: Provide confidence that the data being supplied to AML models meets expected quality standards before it is consumed by the models.
• Preventive controls / monitoring: Move the process from reactive detection to preventive monitoring so issues are caught earlier in the data lifecycle.

Model and data ownership

• Demonstrated accountability for analytical or quantitative models across implementation, maintenance, and controlled change processes.
• Experience operating within governed environments requiring formal documentation, controls, and audit readiness.
• Ability to independently challenge model assumptions and interpret outputs without serving as primary model developer.
• Proficient in performing data analysis and validation using SQL in Teradata environments.
• Ability to analyze large datasets to identify trends, issues, and insights supporting business decisions.
• Experience monitoring, validating, and reporting on data quality metrics including accuracy, completeness, and timeliness.
• Strong capability to conduct root cause analysis for data quality issues.
• Demonstrated experience partnering with stakeholders to drive resolution of data defects and control gaps.
• Proven experience managing complex projects with multiple stakeholders across technology, data, and business teams.
• Ability to coordinate timelines, deliverables, dependencies, and risk issues to successful completion.

EEO:

“Mindlance is an Equal Opportunity Employer and does not discriminate in employment on the basis of – Minority/Gender/Disability/Religion/LGBTQI/Age/Veterans.”