Data Operations Analyst

Job not on LinkedIn

🔥 3 minutes ago

🇺🇸 United States – Remote

💵 $80k - $110k / year

⏰ Full Time

🟢 Junior

🟡 Mid-level

📉 Data Analyst

👻 Ghost score 0%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Brightfield

WebsiteLinkedInAll Job Openings

51 - 200 employees

Founded 2006

💼 Consulting

📦 Logistics

🏥 Healthcare

Consulting • Logistics • Healthcare

Brightfield is a leading provider of extended workforce market intelligence, utilizing its AI platform, TDX, to help global businesses identify and realize savings opportunities in contingent workforce spending. By automating time-consuming tasks and enabling insightful SOW analysis, Brightfield empowers organizations to negotiate supplier contracts with greater certainty and achieve significant ROI across various industries, including healthcare, technology, and financial services.

📋 Description

• Analyze workforce and business data to identify trends, patterns, and opportunities • Investigate customer questions and business challenges using a structured analytical approach • Translate business needs into data-driven solutions and recommendations • Identify anomalies, inconsistencies, and potential issues within datasets • Support development of customer deliverables and reporting solutions • Work directly with customers to understand business objectives and reporting requirements • Participate in customer meetings and presentations • Present findings and recommendations clearly and actionably • Provide timely updates on deliverables and project status • Build trusted customer relationships through responsiveness and follow-through • Ensure data accuracy, consistency, and completeness across datasets and deliverables • Perform quality assurance reviews of analyses and reports before customer delivery • Investigate and resolve data discrepancies • Maintain organized documentation of methodologies, assumptions, and findings • Manage multiple projects and customer requests simultaneously • Prioritize work in a fast-paced environment and adapt to changing priorities • Collaborate with Customer Success, Product, Data, Data Analyst, and Platform Engineering teams • Develop business and industry understanding to inform analytical solutions • Stay current with data-analysis trends, tools, and best practices; share knowledge with the team • Identify automation opportunities and develop internal tools and automations using Python and SQL

🎯 Requirements

• Bachelor's degree in a relevant field (e.g., Business, Analytics, Statistics, Mathematics, Economics) or equivalent work experience • 2+ years of experience in data analysis, business analysis, consulting, customer-facing analytics, or a related role • Experience working directly with customers, clients, or business stakeholders • Demonstrated ability to solve business problems using data • 2+ years of Dev-Ops, internal tools development, or full stack systems engineering, with an emphasis on automation • Strong written and verbal communication skills • Ability to explain analytical findings to non-technical audiences • Confidence participating in customer meetings and presentations • Ability to listen actively, ask clarifying questions, and translate customer requirements into analytical solutions • Advanced proficiency in Excel, including Pivot Tables, XLOOKUP/VLOOKUP, INDEX/MATCH, logical formulas, and data validation • Proficiency in Python, Docker, Git, and large dataset manipulation • Proficiency in SQL for data extraction and analysis • Experience preparing reports, analyses, and customer-facing deliverables • Strong problem-solving and critical-thinking abilities • Strong attention to detail and commitment to data quality • Ability to identify trends, anomalies, inconsistencies, and actionable insights within datasets • Ability to manage multiple priorities and deliver accurate, high-quality work