Data Analyst (Data Science & Governance) in Sunnyvale, CA _Onsite only on w2 and GC

Key Responsibilities: Data Science & Analytics: Have familiarity with designing, developing and deploying statistical models, machine learning algorithms, and analytical framework to support channel business decisions Have hands on experience in conducting exploratory data analysis to surface insights on sales performance, inventory Have familiarity with building an maintaining forecasting models Translate complex analytical outputs in clear, actionable recommendations for business audience Data

Role-Need Profiles || Data Analyst - Data & Reporting Location-Cupertino, CA- Onsite Day 1 Duration :12+ Months Job Tittle: Data Steward/ Scientist Location- Cupertino (Contract) We are looking for a rare blend of analytical depth, data ownership mindset, and modern AI fluency. As a senior data steward & scientist you will sit at the intersection of advance analytics, knowledge representation, data governance and intelligent automation - helping us unlock the full value of our data assets whole

Job Description: Responsibility: Perform root cause analysis on processes and data to identify opportunities for improvement and answer questionsBuild processes that support data transformation, workload management, data structures, dependency and metadataPerform data validation checks, identify and rectifying errors, and maintaining a quality standard throughout the data's lifecycle. Explore datasets to identify trends, patterns, and insights. Perform analysis for stakeholders and other non-tec

Job Title: Senior Data Analyst (On-Site) Location: On-Site(San Jose, CA) - 5 days a week to office Experience Required: 8 12 Years Note: Semiconductor Industry experience is mandatory. Job Overview: We are seeking an experienced Senior Data Analyst with strong expertise in data mining and Tableau to join our team in an on-site capacity. The ideal candidate will have 8 12 years of hands-on experience in data analysis, advanced SQL, Tableau dashboard development, and Databricks. Experience in the