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Business Insights & Decision Support will use data to help the business make better decisions across Quality, Software & Services, and Engineering. This role focuses on interpreting analyses, generating insights, and telling the story behind the numbers, rather than heavy coding or data engineering. The ideal candidate is comfortable working with data, but excels at translating results into clear recommendations for business partners.
Job Responsibility:
Partner with business stakeholders to clarify questions, frame problems, and define success metrics.
Translate ambiguous business issues into structured analytical questions and practical approaches.
Use BI tools (e.g., Power BI, Tableau) and statistical methods (e.g., hypothesis framing, sampling, segmentation, variability) to explore data and identify trends, patterns, and anomalies.
Develop and interpret descriptive and diagnostic analyses (e.g., trends over time, segmentation, cohort analysis, root cause analysis).
Connect analytical findings to business context and clearly explain “what this means” and “what to do next.”
Synthesize analyses into clear narratives and executive-ready communications tailored to non-technical audiences.
Communicate trade-offs, limitations, and assumptions in a way that supports sound decision-making.
Facilitate discussions around insights, align actions, and track follow-up results.
Identify opportunities to improve data quality, metric definitions, and reporting consistency in partnership with IT/data engineering.
Document analytic approaches, business logic, and metric definitions for reuse and transparency.
Requirements:
7+ years of experience
BA or BS in relevant field or equivalent real-world experience
Solid understanding of statistical concepts applied to business decisions (e.g., distributions, sampling, variability, correlation vs. causation, and practical significance).
Demonstrated ability to interpret data and explain insights to non-technical audiences.
Strong written and verbal communication skills, with experience creating clear, concise presentations for stakeholders.
Experience in a business-facing analytics role supporting operations, product, quality, or customer experience.
Experience working with large or complex datasets and collaborating with data engineers/IT for data access and structure (without needing to own pipelines).
Proven cloud experience and familiarity with at least one cloud platform (Azure preferred)
Business Acumen: Ability to quickly understand business processes and connect insights into financial and operational outcomes.
Critical Thinking: Comfortable challenging assumptions, probing for root causes, and weighing multiple explanations.
Data Storytelling: Skilled at turning analyses into clear narratives with a logical flow from question → approach → findings → implications → recommendations.
Collaboration: Works effectively with cross-functional partners, including business leaders, IT, and data engineering.
Action Orientation: Focused on outcomes and decisions, not just reports
drives follow-through on insight-driven actions.
Nice to have:
Master’s degree in Statistics, Mathematics, Industrial Engineering, or Business Analytics
Experience in manufacturing, automotive, or industrial environments, or other data-rich operational settings.
Experience with tools such as Databricks, python, and SQL