About:

• Location: Sunnyvale, CA
• Contract: 6+ months

Technical Skills:

• Proficiency in programming languages such as Python or R.
• Proficiency in statistical/empirical model building
• Extensive experience with time series data, analysis, and modeling
• Strong knowledge of statistical principles and machine learning techniques (e.g., regression, classification, clustering, neural networks)
• Experience with data manipulation and analysis using libraries such as pandas, NumPy, and SciPy
• Familiarity with data visualization tools (e.g., Matplotlib, Seaborn)
• Experience with SQL and relational databases
• Knowledge of big data technologies (e.g., Hadoop, Spark) is a plus

Additional Skills (Preferred):

• Experience in deploying AI-based solutions in manufacturing environment
• Experience with cloud platforms (e.g., AWS, Google Cloud, Azure)
• Familiarity with version control systems (e.g., Git)

Key Responsibilities:

• 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

Must have:

• 5+ years of experience in data science, analytics, or a related field.
• Master's or Ph.D. degree in Data Science, Statistics, Computer Science, or a related field.
  Experience on applications in Manufacturing desirable.
• Proficiency in programming languages such as Python or R.
• Proficiency in statistical/empirical model building
• Extensive experience with time series data, analysis, and modeling
• Strong knowledge of statistical principles and machine learning techniques (e.g., regression, classification, clustering, neural networks)
• Experience with data manipulation and analysis using libraries such as pandas, NumPy, and SciPy
• Familiarity with data visualization tools (e.g., Matplotlib, Seaborn)
• Experience with SQL and relational databases
• Knowledge of big data technologies (e.g., Hadoop, Spark) is a plus