Data Scientist/Analyst

With more than 120 operations and approximately 20,000 employees worldwide, Precision Castparts Corp. is the market leader in manufacturing large, complex structural investment castings, airfoil castings, forged components, aerostructures and highly engineered, critical fasteners for aerospace applications. In addition, we are the leading producer of airfoil castings for the industrial gas turbine market. We also manufacture extruded seamless pipe, fittings, and forgings for power generation and oil & gas applications; commercial and military airframe aerostructures; and metal alloys and other materials for the casting and forging industries. With such critical applications, we insist on quality and dependability – not just in the materials and products we make, but in the people we recruit.

PCC is relentless in its dedication to being a high-quality, low-cost and on-time producer; delivering the highest value to its customers while continually pursuing strategic, profitable growth.

In 2016, Berkshire Hathaway, led by Chairman and CEO Warren E. Buffett, acquired Precision Castparts Corp.

Mission:

Reviews, analyzes, evaluates engineering/business data to identify hidden patterns in data and operationalizes these insights to reduce costs, minimize defects, and increase productivity. Participates and formulates data systems to support overall business intelligence strategies. Collaborates with data stakeholders to develop statistical models, create algorithms for predictive analysis, organize disparate datasets, participate with DBAs in data extraction/transformation, and develop data architectures. Deliver presentations and solutions to stakeholders and management. The Data Scientist also works on identifying patterns requiring a broad understanding of statistical and machine learning techniques, in addition to advanced capabilities to extract, clean, and transform raw data for predictive modeling. Operationalizing the predictive insights often requires deploying predictive scoring systems and data visualization tools to make the insights actionable. Maintain knowledge of current data management technology and methodologies to recommend advanced solutions consistent with company and departmental objectives.

Duties:

• 
  Collecting data through means such as analyzing business results or by setting up and managing new studies
• Build, deploy, and monitor predictive models, scoring systems, and recommendation engines
• Prepare data and build data pipelines as necessary
• Provide business-friendly explanations for the decisions arrived at by machine learning models
• Building tools to automate data collection including programming in (R, Python, etc)
• Develop methodologies and processes for prioritization and scheduling of projects
• Proficient implementation of algorithms and statistical models
• Creating reports and presentations for business uses. Partner with business unit leadership to provide strategic recommendations to maximize the value of information assets via their creation, access, and use
• Correlating similar data to find actionable results
• Support data governance and master data initiatives
• Support efforts for integrating and centralizing multi-plant/system data into a central data lake to meet data analytics objectives
• Off-shift and weekend application and systems support.

Requirements:

• 
  Master’s degree in Operations Research, Industrial Engineering, Applied Mathematics, Statistics, Physics, Computer Science, or related fields
• Knowledge of database design including relational structure, OLTP, Star Schemas, and ETL methodologies.
• 5-7 years of professional experience.
• Experience working in a big data framework
• Proficient with SQL and one or more data science scripting languages (Python or R preferred).
• Deep understanding of a variety of statistical/machine learning techniques, including regression, decision trees, neural networks, SPC, etc.
• Strong understanding of database systems, including relational, time-series, and NoSQL
• Demonstrated experience applying data science methods to real-world data problems
• Experience utilizing visualization tools to take advantage of the growing volume of available information
• Outstanding work ethic and willingness to work extended hours to resolve operation critical problems.