Data Analytics Consultant

MeridianLink is seeking a Data Analytics Consultant who brings strong project management discipline to complex, client-facing analytics engagements. This role sits at the intersection of analytics delivery, client partnership, and cross-functional execution. You will own analytics initiatives from intake through delivery, managing scope, timelines, dependencies, and stakeholder expectations while ensuring high-quality, actionable outputs. In this role, you will lead multiple concurrent analytics projects for financial institutions, coordinating across internal teams and client stakeholders to translate business objectives into well-defined analytical deliverables. You will be responsible for driving projects forward, removing blockers, and ensuring work is delivered accurately, on time, and aligned to client goals. While technical analytics skills are essential, success in this role depends equally on your ability to plan work, communicate clearly, manage risk, and guide clients through complex decisioning and performance insights. As a highly visible member of the Analytics Team, you will serve as both delivery lead and trusted advisor, helping clients understand how MeridianLink decisioning products and analytics capabilities support better lending outcomes. If you thrive in a fast-paced environment, enjoy owning projects end to end, and take pride in delivering polished, client-ready work, this role offers the opportunity to make a measurable impact across our customer base. Key Responsibilities:

• Learn and develop a strong understanding of MeridianLink Decision Engines, including MeridianLink Consumer and DecisionLender, how applications are processed end to end, and how to navigate the user interface in order to guide clients on where key modules and functionality live within the product environment.
• Analyze complex datasets to identify key trends, evaluate performance, and deliver insights that inform business decisions.
• Design and maintain interactive dashboards that provide clients with real-time visibility into performance metrics.
• Use business intelligence tools such as Power BI and Sisense to develop custom reports aligned with client goals.
• Lead client-facing meetings to present findings and translate data into actionable business recommendations.
• Work collaboratively with internal teams to design and deliver analytics solutions that drive value.
• Ensure accuracy, consistency, and timeliness across all analytics deliverables.
• Contribute to internal knowledge-sharing and support team growth through peer collaboration and training.
• Develop new analytics capabilities, including automation and scalable reporting tools.
• Serve as a trusted advisor to clients, offering insights on best practices in analytics tools and strategy.
• Build and maintain all marketing collateral, analytics case studies, and blogs for customer engagement
• Communicate complex technical findings in a clear and compelling way to both technical and non-technical stakeholders.

Qualifications:

• Bachelor’s Degree in Data Analytics, Computer Science, Statistics, Economics, Finance, or Mathematics is preferred.
• 3-6 years of relevant experience in business intelligence, analytics, or data analysis. Experience working at a financial institution is preferred.
• Lead end-to-end project execution, developing detailed project plans, timelines, and resource allocations to ensure on-time, on-budget delivery while managing scope, risks, and dependencies. PMP or other project management certification is highly desirable.
• Drive cross-functional coordination and accountability, facilitating clear communication, tracking milestones and deliverables, and proactively resolving issues to maintain alignment with business objectives.
• High-level proficiency with business intelligence tools such as Power BI or Sisense for analytics and reporting.
• Strong skills in Microsoft Excel and PowerPoint for data analysis and presentation.
• Expert-level skills in writing and optimizing complex SQL queries for data extraction and transformation. Strong skills in Python for data processing, transforming, and manipulation are also preferred.
• Exceptional attention to detail with the ability to manage multiple projects and meet tight deadlines.
• Strong communication and interpersonal skills, with the ability to work effectively in cross-functional teams and present complex data insights to stakeholders.

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