Business Consultant Specialist

LexisNexis Risk Solutions•Alpharetta, GA

About The Position

LexisNexis Risk Solutions is the essential partner in the assessment of risk. Within our Business Services vertical, we offer a multitude of solutions focused on helping businesses of all sizes drive higher revenue growth, maximize operational efficiencies, and improve customer experience. Our solutions help our customers solve difficult problems in the areas of Anti-Money Laundering/Counter Terrorist Financing, Identity Authentication & Verification, Fraud and Credit Risk mitigation and Customer Data Management. The Business Services team partners closely with technology, operations, and product groups to ensure our platforms are reliable, observable, and continuously improving. We focus on operational intelligence, early issue detection, and translating data into meaningful action for the business. This role sits at the intersection of data science, platform monitoring, and customer experience—responsible for translating complex product usage data into actionable insights, alerts, and proactive interventions that protect revenue and improve platform health. As a core member of the Operational Intelligence team, this role partners closely across technology and operations to deliver real-time visibility, anomaly detection, and rapid response capabilities across product platforms.

Requirements

Advanced SQL (required) with hands-on experience querying large-scale, high-velocity datasets
Experience working with distributed data platforms (e.g., Databricks, Spark, or similar)
Experience building or tuning anomaly detection, forecasting, or pattern recognition models
Ability to operationalize models into alerting or reporting systems (not just notebooks)
Experience designing or supporting alerting frameworks tied to system or business thresholds
Proven ability to build actionable dashboards (Power BI, Kibana, etc.)
Demonstrated ability to investigate anomalies, trace issues across systems, and identify root causes
Experience translating data signals into clear operational or business impacts
Ability to work directly with operations, product, and engineering teams
Converts ambiguous business needs into structured data/analytics solutions
Experience improving alert logic, reducing false positives, and scaling analytics workflows
Ability to document data models, dashboards, and alerting logic for reuse and maintainability
Operates as a long-term owner of analytics assets—not just a builder

Nice To Haves

Applied Data Science / ML Exposure (Practical > Theoretical)
Familiarity with tools like Elastic, Kibana, Splunk, or similar observability platforms
Focus on usability, surfacing signals vs. noise for operational teams
Exposure to scripting (Python preferred) for data processing or automation

Responsibilities

Analyze large-scale usage datasets using SQL and data science methodologies to identify trends, patterns, and anomalies in product platform activity.
Design, develop, and deploy AI models that automatically dashboard active usage and flag abnormal patterns in real time.
Build and maintain operational alerts, interactive dashboards, and visualization solutions using Databricks, Elastic AI, Kibana, PowerBI, and related tools.
Create data profiles and leverage them to generate timely, actionable analytics that support rapid business decision-making and operational response.
Partner closely with operations teams to establish and refine early-escalation workflows for customers experiencing issues with our product platforms.
Continuously monitor platform health metrics, perform root-cause analysis on usage anomalies, and recommend data-driven improvements to alerting logic and dashboards.
Collaborate with cross-functional stakeholders to translate business requirements into technical analytics solutions that deliver clear operational value.
Document analytics processes, model logic, and dashboard architectures to ensure knowledge sharing and long-term maintainability of the Operational Intelligence platform.
Stay current with emerging tools and best practices in data science, AI-driven monitoring, and business intelligence to drive continuous innovation within the team.