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Data Scientist || Sunnyvale, CA || 10+ years || PP number mandatory

Please go through below JD and share with me suitable profiles.

 

Title: Data Scientist
Location: Sunnyvale, CA
Duration: 6 months

“? Education: Masters or Ph.D. degree in Data Science, Statistics, Computer Science, or a related field.? Experience: 5+ years of experience in data science, analytics, or a related field.? Experience on applications in Manufacturing desirable. Technical Skills:o Proficiency in programming languages such as Python or R. o Proficiency in statistical/empirical model buildingo Extensive experience with time series data, analysis, and modelingo Strong knowledge of statistical principles and machine learning techniques (e.g., regression, classification, clustering, neural networks).o Experience with data manipulation and analysis using libraries such as pandas, NumPy, and SciPy.o Familiarity with data visualization tools (e.g., Matplotlib, Seaborn).o Experience with SQL and relational databases.o Knowledge of big data technologies (e.g., Hadoop, Spark) is a plus.? Additional Skills (Preferred):? Experience in deploying AI based solutions in manufacturing environment.o Experience with cloud platforms (e.g., AWS, Google Cloud, Azure).o Familiarity with version control systems (e.g., Git).? Data Analysis: Analyze large, complex datasets to identify trends, patterns, and insights that inform business decisions.? Model Development: Develop, implement, and validate predictive models and machine learning algorithms to solve various business problems.? Data Cleaning: Preprocess and clean data to ensure its quality and integrity before analysis.? Visualization: Create data visualizations and dashboards to communicate findings to stakeholders in a clear and concise manner.? Collaboration: Work closely with cross-functional teams, including engineering, product management, and marketing, to understand their data needs and provide relevant insights.? Reporting: Generate comprehensive reports and presentations that summarize key findings and recommendations.”

~NumPy, and SciPy, time series data, analysis, and modeling~

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