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.

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