Senior Business Intelligence Analyst

Concentrix•Usa, TN

12h•Remote

About The Position

Join our award-winning One Concentrix team as a BI Analyst supporting one of the world's most innovative AI-native technology companies. This role operates at the intersection of AI, customer outcomes, partner performance, and business transformation in a fast-paced, high-growth environment where speed, ownership, and execution matter. ABOUT CONCENTRIX At Concentrix, we help the world's best brands build exceptional customer experiences through innovative technology, operational excellence, and human-centered solutions. As organizations accelerate adoption of AI, automation, cloud technologies, and digital transformation initiatives, Concentrix partners with clients and strategic ecosystem partners to deliver measurable business outcomes at scale. We are seeking a BI Analyst to drive the help successful delivery, adoption, and expansion of partner-led AI solutions while ensuring customers achieve meaningful business value and long-term success. Success in this role requires comfort operating in a highly dynamic, rapidly evolving environment where priorities shift quickly, new challenges emerge daily, and ambiguity is often present. The ideal candidate thrives in an AI-native culture, demonstrates strong initiative, embraces continuous learning, and can quickly evaluate information, make sound decisions, and drive execution without waiting for direction.

Requirements

5 + years of experience in business intelligence, sales analytics, business analytics, revenue operations, sales strategy or a related analytical role.
Demonstrate success turning data into commercial insights and practical business recommendations, rather than primarily producing reports.
Bring practical knowledge of B2B or SMB sales motions, including pipeline management, acquisition, activation, conversion, adoption, retention and growth.
Demonstrate experience partnering directly with Sales leaders or client stakeholders in a fast-paced environment.
Communicate executive-ready insights and influence senior stakeholders through clear, concise business narratives.

Nice To Haves

Added Experience in software, SaaS, technology, partner-led sales or another complex B2B commercial environment.
Hands-on experience using AI platforms in analytical work.
Experience automating recurring analysis, prototyping lightweight analytical tools or improving data workflows.
Experience combining quantitative data with qualitative or unstructured information to identify themes, sentiment or knowledge gaps.
Experience establishing reporting, decision frameworks and operating rhythms in a build-and-run environment.
Familiarity with revenue operations, sales plays, partner performance, adoption, activation and campaign-effectiveness analytics.

Responsibilities

Serve as a trusted analytical partner and extension of SMB Sales leadership, providing an independent, data-informed point of view.
Translate data into clear recommendations that influence sales strategy, prioritization, resource allocation and frontline execution.
Support Sales leadership with planning, forecasting, pipeline reviews, performance management and strategic decision-making.
Identify where the business is winning, losing, accelerating, stalling or underperforming.
Segment performance across markets, customer groups, industries, products, channels, sellers, partners, funnel stages and opportunities.
Move beyond reporting what happened to determine why it happened, what it means commercially and what Sales should do next.
Identify emerging trends, risks, execution gaps and growth opportunities before they become visible through standard reporting.
Develop and test hypotheses, challenge assumptions and proactively investigate areas of business opportunity or risk.
Partner directly with Sales leaders, clients, operational teams and cross-functional stakeholders to clarify objectives and define the appropriate analytical approach.
Manage client communication and expectations across competing priorities, changing requirements and evolving business needs.
Communicate complex analytical findings simply and confidently to technical and non-technical audiences.
Move comfortably between detailed analysis and high-level commercial discussions.
Use advanced AI capabilities, to structure ambiguous business problems, analyze information, generate hypotheses and accelerate insight development.
Use AI coding tools to support SQL development, automate repetitive analysis, build lightweight tools and improve data workflows.
Apply AI-assisted methods to structured and unstructured information, including qualitative feedback, conversation outputs and operational notes, when appropriate.
Identify opportunities to automate recurring reporting, data preparation and analytical workflows.
Validate AI-generated outputs and maintain strong standards for analytical accuracy, confidentiality, data integrity and responsible AI use.
Operate effectively in a fast-moving, startup-like environment where processes, systems, requirements and success measures may not be fully defined.
Create structure from incomplete information and independently determine a practical path forward.
Demonstrate curiosity and creativity by exploring data, asking strong questions and proposing new approaches to business problems.
Prioritize quickly, balance speed with analytical rigor and adapt as business needs evolve.
Take ownership from problem definition through analysis, recommendation, stakeholder alignment and follow-through.
Work with structured and unstructured information from multiple sources and clearly communicate data limitations, assumptions and quality gaps.
Develop dashboards and decision-support tools that allow Sales leaders to quickly understand performance and determine the required action.
Apply appropriate statistical methods to evaluate segmentation, trends, variation and performance relationships.
Move recurring reporting toward more diagnostic, predictive and action-oriented insights.
Maintain the consistency, accuracy and reliability of reporting, business metrics and underlying data.