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The Senior Analytics and Platform Analyst will play an important role in driving data-driven decision-making and digital enablement across the organization. You are responsible for delivering actionable insights through a combination of Data Analysis and Insights Generation, Platform Management and Optimization, apply practices for data governance and ETL, Lead projects using machine learning, statistical modeling, and AI analytics for problems like predictive models or anomaly detection. Collaborating with business and IT teams, the analyst will help enable scalable data, analytic solutions - for initiatives in manufacturing operations, supply chain, sales, and product development to improve operational efficiency, and customer/market insights, across the manufacturing value chain.
Job Responsibility:
Analyzing manufacturing data to create dashboards, reports, and predictive models that identify trends and support optimizations in production, supply chain, and inventory
Managing analytics platforms like Power BI, and Databricks, ensuring data integrity, scalability, security, and effective ETL processes
Collaborating with cross-functional teams in manufacturing, Engineering ops, Marketing & sales involves translating business needs into technical solutions and providing data-driven recommendations for process improvements and cost reductions
Supporting the integration and optimization of cloud-based data platforms, collaborates with cross-functional teams to define data requirements, and ensures data quality and governance standards are met
Promoting analytics self-service, supporting tool adoption, and contributing to the ongoing evolution of the enterprise analytics ecosystem
Leading advanced analytics projects with machine learning and AI for tasks like predictive maintenance, maintaining data quality and compliance, mentoring junior analysts, and monitoring KPIs to present insights to leadership
Requirements:
Bachelor's degree in Data Science, Computer Science, Industrial Engineering, Statistics, or a related field
5+ years in data analytics, with at least 3 years in a senior or lead role
Proficiency in SQL, Python, R, or similar languages for data manipulation and analysis
Expertise in analytics platforms and tools (e.g., Power BI, AWS/GCP/Azure cloud services, Databricks)
Knowledge of data lakehouse and warehousing architectures, ETL processes, data management practices
Experience with statistical modeling, machine learning frameworks (e.g., scikit-learn, TensorFlow), and visualization techniques
Problem-solving abilities, communication skills for presenting data to non-technical audiences, and ability to work in teams
Nice to have:
Master’s degree in Data Science, Computer Science, Industrial Engineering, Statistics, or a related field
Certification in data analytics or platforms (e.g., Google Data Analytics, Microsoft Certified: Azure Data Engineer, Optimizely, Amplitude, etc.)
Experience with IoT data from industrial equipment or SAP, Salesforce, Windchill, etc.
Familiarity with lean manufacturing principles or Six Sigma methodologies
Record of implementing analytics solutions with business impacts, such as cost savings or efficiency gains
Experience in manufacturing, consumer goods, or industrial sectors