Lead Data Analyst

Ascentt is building cutting-edge data analytics & AI/ML solutions for global automotive and manufacturing leaders. We turn enterprise data into real-time decisions using advanced machine learning and GenAI. Our team solves hard engineering problems at scale, with real-world industry impact. We’re hiring passionate builders to shape the future of industrial intelligence. Lead Data Analyst Key Responsibilities Lead the end-to-end analytics lifecycle for cost-focused projects, from defining key objectives to delivering insights and recommendations to senior stakeholders. Lead and contribute to analytics initiatives with a focus on cost metrics, ensuring alignment with business goals. Data Strategy: Define and implement robust data models, ensuring the scalability and accuracy of cost metrics for reporting and forecasting. KPI Development: Design, measure, and monitor cost-related KPIs, including cost-per-unit, cost-of-service, budget utilization, and return on investment (ROI). Insights Delivery: Create dashboards and reports that effectively communicate cost metrics and trends to stakeholders, enabling data-driven decisions. Advanced Analysis: Conduct exploratory data analysis, trend forecasting, and scenario modeling to identify cost-saving opportunities and potential risks. Data Governance: Ensure data quality, integrity, and compliance by working closely with data engineering and governance teams. Data Exploration: Analyze datasets to uncover trends, patterns, and insights that help the business better understand cost dynamics. Collaborate Across Teams: Work closely with Finance, Operations, and other departments to align analytics with organizational needs and goals. Ensure Data Quality: Partner with data engineers and other team members to ensure the accuracy and reliability of data. Contribute to Team Growth: Share knowledge and insights with team members to foster a collaborative and innovative work environment. Qualifications Bachelor’s or Master’s degree in Data Science, Economics, Finance, Statistics, or a related field. 8+ years of experience in data analytics, with demonstrated expertise in cost analytics, financial modeling, and cost optimization. Proficiency in data analysis tools and languages such as SQL, Python, or R. Hands-on experience with BI tools like Tableau, Power BI, or Looker. Strong understanding of database systems, data warehousing, and ETL processes. Strong analytical mindset with the ability to transform complex data into actionable insights. Excellent written and verbal communication skills, with experience presenting findings to stakeholders. Ability to manage multiple priorities and deadlines in a fast-paced environment. Show more Show less