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Data Scientist

Description


What You Will Do In Your Role

  • Work with a team of data scientists/engineers and cross functional partners to collaboratively develop solutions 
  • Bring an entrepreneurial mindset, openness, transparency, and collegiality to your everyday work 
  • Develop and deploy statistical and ML pipelines starting with structured and unstructured data, including continuous model testing and maintenance 
  • Utilize process control methods, anomaly detection algorithms, and optimization approaches for process improvement in manufacturing 
  • Consult with Business Analysts and customers to understand customer facing opportunities and needs 
  • Collaborate with manufacturing and technology to define data architecture that meets both present and future goals of the business 
  • Provide advanced analytics and ML expertise in the design and delivery of data products for broad consumption by business partners 
  • Mentor and support the training of technical and non-technical teams in development in data science and machine learning 
  • Participate in the broader data science community to stay current with methodology, software, and data development and availability 
  • Communicate and visualize the output of analyses, including both written and verbal communication, to business leaders and non-technical audiences 
  • Conceptualize and deploy data science solutions for business questions 
  • Identify analytics enhancement opportunities for existing advanced analytics tools 
  • Create high performance, web-based, visual analytics products using powerful, contemporary tools 
  • Share and implement innovative new ideas; optimize existing products in highly collaborative team environment (i.e. code optimization) 
  • Contribute to the design of and articulate data model requirements for your products 
  • Knowledge and experience with all key data domains (e.g., Customers, Products, Vendors, Supply Chain, etc.) 
  • Experienced in evaluating data requirements, developing data standards and integration approaches and alternatives 
  • Experienced at designing data management/stewardship organizations and development of business cases associated with improved data quality 
  • Effective communication and collaboration skills 


The Experience You Will Bring

Requirements:

  • Bachelor’s degree in a computational and quantitative discipline (e.g. mathematics, statistics, computer science) 
  • A minimum of 3-5 years industry experience in applying data science to solve problems in manufacturing and supply chain space 
  • Deep expertise in machine learning including hands on experience with most of the following methods: regression techniques, neural networks, decision trees, clustering, pattern recognition, dimensionality reduction 
  • Proven experience in applied statistics and ML in a business setting, and command of the typical use cases in the field 
  • Strong understanding of the tools of the trade, including a variety of modern programming languages (R, Python, JavaScript) and open-source technologies (Linux, TensorFlow, Hadoop, and Spark) 
  • Knowledge of database and visualization tools (e.g. SQL, Tableau, Power BI, HTML, CCS, Dash, Flask, Django) 
  • Proven experience building industrialized analytics tools working in an AWS ecosystem (AWS database connections, real-time streaming) 
  • Comfort working and communicating with non-technical teams to translate business questions to analytically actionable questions, and a strong desire to build meaningful solutions for a manufacturing centered business 
  • Ability to independently set goals, complete deliverables, and collaborate and with teams within and across functions 
  • Fluent in English language 


What Will Put You Ahead

  • Previous experience with Molding, Metal stamping, Plating, Optoelectronics, and SMT manufacturing processes 
  • Experience in real-time analysis of time series data. 


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