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Open nowPosted 79 days ago

Pricing- Manager, Data & Analytics, Business & Operations

bluelinx143 open roles

Where
1950 Spectrum Cir, Marietta, GA 30067, USA
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Your applicationOpen nowPricing- Manager, Data & Analytics, Business & Operationsbluelinx · 1950 Spectrum Cir, Marietta, GA 30067, USA

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This job: posted 79 days ago

The posting

Position Purpose Summary:  The Senior Data Manager (Pricing) is a hands‑on data science leader who partners with the Pricing organization to drive margin expansion, visibility, and decisioning through analytics products. This role functions as the primary data science and BI leader supporting pricing workflows, including dashboards, performance reporting, and scalable analytics tools. The Senior Data Manager leads by influence across stakeholders, establishes analytic standards, and ensures pricing teams have reliable, actionable insights—especially through Power BI solutions and Python-based data pipelines. Key Tasks/Responsibilities: Analytics Leadership & Functional Management:

Serve as the functional analytics leader for the Pricing department, translating pricing priorities into a scalable analytics roadmap and delivery plan. Establish standards for metric definitions (e.g., margin, price realization, overrides), dashboard governance, and reporting cadence across Pricing stakeholders. Lead cross-functional collaboration with Pricing, Category, Sales leadership, and IT/data teams to prioritize, deliver, and sustain analytics products

Power BI & Dashboard Development:

Design, build, and maintain enterprise-grade Power BI dashboards for pricing performance, margin trends, and operational tracking (e.g., progress monitoring, completion status, exception visibility). Create semantic models and governed datasets to ensure consistency of insights and reduce report sprawl; improve usability and self-service for pricing stakeholders. Partner with stakeholders to define KPIs, build executive-ready views, and evolve dashboards based on field feedback and adoption.

Data Science & Python Enablement:

Use Python to develop repeatable analytics workflows (data preparation, modeling, anomaly detection, forecasting, and performance monitoring) that support pricing strategy and governance. Build automated pipelines and analysis templates to reduce manual work and improve timeliness/accuracy of pricing insights. Apply statistical and analytical techniques to uncover margin leakage drivers and identify actionable opportunities for pricing and category teams

Data Quality & Enablement:

Improve data integrity and usability by partnering with master data and business teams on product attributes and category structures needed for pricing segmentation and maintenance Support data cleanup initiatives by designing tracking and reporting mechanisms

Tooling, Scalability, & Pricing Platform Support:

Support evaluation and enablement of pricing platforms and analytics integration, ensuring pricing data can be consumed effectively via BI tools (including Power BI) and analytics layers. Develop repeatable reporting packages for leadership and business reviews; ensure metrics align to Pricing profitability goals and strategic initiatives

  Knowledge/Skills/Abilities:

Advanced experience in Power BI (data modeling, DAX, semantic layer design, performance tuning) Strong proficiency in Python for analytics and automation (e.g., pandas, numpy, notebooks, productionizing workflows) Proven ability to lead cross-functional work through influence (functional management), driving standards and adoption Strong communication skills with the ability to translate technical findings into business actions Experience supporting Pricing, Revenue Management, or Commercial Analytics organizations in a multi-branch/multi-region environment Experience building dashboards and tracking mechanisms for operational processes and data completeness initiatives Familiarity with pricing governance concepts (overrides, discounting controls, margin leakage visibility)  Experience integrating analytics with enterprise systems and/or pricing platforms; exposure to BI tool interoperability expectations

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