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.