Job Description:
TTI Floorcare has an opening in the Anderson, SC corporate office for a Quality Data Analyst (Power BI & Analytics).
We offer competitive wages and a comprehensive benefits package -- tuition assistance, 401(k), medical/dental/vision coverage, vacation, and holidays.
The Quality Data Analyst plays a critical role in transforming quality data into actionable insights that drive performance, traceability, quality, and continuous improvement across global systems. As part of a world class company and a global Quality organization, this role combines expertise in data analytics, data systems, and business analysis to support New Product Development (NPD) and continuous improvement initiatives—delivering clear, decision-ready insights that can be understood by both technical and non-technical audiences.
Specific duties include:
Power BI Reports (Reporting & Visualization)
- Design and implement Power BI dashboards and reporting tools to monitor key quality KPIs combining data from different sources such as return rates, warranty claims, consumer stars, and supporting data to paint a clear picture of product health and enabling rapid root cause analysis.
- Translate complex datasets into clear visualizations and insights to guide improvement activities, including the ability to communicate findings effectively to lay audiences and business stakeholders.
- Author and maintain report-layer assets in Power BI, using DAX and Power Query (M) as appropriate for report-level transformations and measures.
- Work in a Power BI Project (PBIP) and source-controlled environment.
Analytics (Statistics, Business Analysis, Insight Generation)
- Apply statistical methods to uncover process trends, detect anomalies, and enable data-driven decision making across quality data streams to quantify performance drivers, and to explain “what changed” and “why it matters.”
- Develop predictive models for defects, warranty claims, and service trends to drive proactive improvements.
- Collaborate with quality and service teams to analyze feedback loops and enhance product reliability.
- Support NPD launch readiness by building analytical baselines and monitoring stability during ramp-up.
- Leverage evolving AI capabilities to accelerate analysis and insight discovery, while maintaining sound analytical judgment and clear interpretation of results.
Education and Experience Requirements
- Bachelor’s degree in engineering, data science, or related field required.
- Strong proficiency in Power BI and experience authoring DAX measures.
- Knowledge of statistical analysis and process control concepts, applied to quality outcomes and business decision-making (e.g., trend/variance analysis, anomaly detection, segmentation).
- Demonstrated ability to analyze large, complex datasets and develop actionable insights that translate into measurable outcomes.
- Strong communication skills with demonstrated ability to explain analytics to lay audiences, including concise written summaries and clear verbal walkthroughs of “what changed, why it matters, and what to do next.”
Recommended Experience
- Working knowledge of Python preferred for analytics and repeatable analysis workflows.
- Familiarity with SAP financial tables and Snowflake.
- Experience using Power Query (M).
- Familiarity with modern quality and service data platforms (e.g., Axion) and the ability to understand data provenance well enough to interpret analytics correctly.
- Experience working in a Power BI Project (PBIP) and source-controlled environment.
Competencies and Personal Attributes
- Data-Driven & Relentless Improvement: Use data to challenge the status quo and drive continuous improvement with speed and urgency.
- Extreme Ownership & Agility: Take full accountability for learning, adapting, and delivering solutions in dynamic environments.
- Solution-Driven Execution: Translate insights into actionable outcomes with urgency and measurable impact.
- One Team & Candid Communication: Foster trust through open dialogue and collaboration, celebrating shared success.
- Curiosity and agility: Adapt to evolving data architectures and advanced AI technologies. Embrace change and innovation to revolutionize processes and deliver breakthrough solutions.
