Advanced Analytics Expert
1 day ago
Sierra, CA, USA
Siemens Energy is seeking a talented Data Scientist to drive innovation and excellence in our manufacturing processes. As a key member of our team, you will collect, clean, and analyze large datasets to identify trends and insights. Your expertise in developing predictive models and machine-learning algorithms will help us optimize manufacturing processes, enhance product quality, and reduce costs. The estimated salary for this position is $160,000 - $190,000 per year.
Your Key Responsibilities
* Collaborate with engineering, production, and quality assurance teams to understand data needs and provide actionable insights.
* Develop and implement predictive models and machine-learning algorithms to optimize manufacturing processes.
* Work with data visualization tools (e.g., Tableau, Power BI) and big-data technologies (e.g., Hadoop, Spark) to communicate complex findings to non-technical partners.
* Implement advanced analytics solutions for supervising and improving manufacturing performance.
* Stay updated with the latest developments in data science and machine learning.
About You
* Bachelor's/Master's degree in Data Science, Statistics, Computer Science, Engineering, or a related field.
* 5+ years of experience as a Data Scientist with a strong preference in a manufacturing, industrial, or heavy industry environment.
* Solid understanding of statistical analysis, machine learning algorithms, and predictive modeling, including AWS Sagemaker.
* Proficiency in programming languages such as Python and SQL.
* Experience with data visualization tools (e.g., Tableau, Power BI) and big-data technologies (e.g., Hadoop, Spark).
Benefits
* Career growth and development opportunities.
* Supportive work culture and a healthy work-life balance.
* Flexible work environment with flex hours, telecommuting, and digital workspaces.
* Competitive total rewards package.
* Flexible benefits and savings programs.
* Rewarding vacation entitlement with the opportunity to buy and sell vacation.
* Parental leave.
* Profit sharing.
* Contribute to our social responsibility initiatives.
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