Senior Data Scientist – Renewable Energy

Recruiter
Location
Other (U.S.), California
Salary
Competitive
Posted
03 Oct 2016
Closes
21 Nov 2016
Ref
2602759
Sector
Oil and Gas
Category
Manufacturing
Contract Type
Permanent
Hours
Full Time
The Senior Data Scientist - Renewable Energy will work as part of a world class team to solve statistical, machine learning, analytical and data mining problems to support the needs of the Digital Renewable businesses. This individual will be focused on solving complex technical problems through employing statistical and analytical models to enable productivity, profitability, and growth.

Essential Responsibilities

In this role you will:
  • Develop advanced analysis algorithms using sensor and turbine performance data to find patterns and relationships governing the condition of wind, solar, and hydro components
  • Develop and validate analytical concepts that reduce the LCOE (Levelized Cost of Energy) of wind turbines by improving asset predictability and performance and driving operational excellence in services
  • Develop processes and tools that predict deterioration and remaining useful life of wind and hydro turbine components
  • Lead complex analytics projects from idea generation to prototype development
  • Work closely with the Systems and Controls teams to integrate analytics into existing system platforms and identify gaps and alternative solutions as needed
  • Work with leadership to shape and develop a multi-year product and analytics roadmap
  • Technically assess potential acquisitions
  • Support Big Data initiatives to integrate GE established solutions into GE Renewables
  • Guide and mentor early- and mid-career team members on data science techniques and application to improve turbine design, performance, and maintainability



Qualifications/Requirements

Basic Requirements
  • Master's degree in Computer Science, Statistics, Operations Research, Applied Math, Engineering or relevant from an accredited college or university
  • Minimum 10 years of experience with analytics, statistics or data science
Eligibility Requirements
  • Legal authorization to work in the U.S. is required. We will not sponsor individuals for employment visas, now or in the future, for this job
  • Any offer of employment is conditioned upon the successful completion of a background investigation and drug screen




Additional Eligibility Qualifications

GE will only employ those who are legally authorized to work in the United States for this opening. Any offer of employment is conditioned upon the successful completion of a background investigation and drug screen.

Desired Characteristics

  • Advanced degree (PhD) in Computer Science, Statistics, Operations Research, Applied Math, Engineering or relevant from an accredited college or university
  • 5+ years of experience with statistical and analytic programming design and technologies (Python, R, Spark, SQL, SAS JMP, etc.)
  • 2+ years of experience with Wind turbine technology, including control and/or loads simulation of wind turbines
  • Proficiency in key statistical techniques (predictive modeling, logistic regression, decision trees, data mining methods, forecasting, neural networks and other advanced statistical and econometric techniques)
  • Applied knowledge of many of these machine learning concepts: supervised/unsupervised learning, regularization, feature selection, regression / classification, cross-validation, bagging, kernel methods, sampling, and probability distributions
  • Ability to apply the specified technologies in concert with physical system modeling and simulations to provide classification, diagnosis, and prediction of system behavior.
  • Extensive hands on experience working with very large data sets, including statistical analyses, data visualization, data mining, and data cleansing / transformation Knowledge about industrial control / SCADA systems
  • Entrepreneurial inclination to discover novel opportunities for applying analytical techniques
  • Experience with development projects and project management
  • Global mindset with ability to effectively lead within a matrixed environment
  • Strong interpersonal and communication skill
  • Fundamental knowledge regarding development of algorithms or analytics
  • Fundamental knowledge on statistical and analytical design and technologies (Python, R, Spark, SQL, SAS JMP, etc.)
  • Familiarity in dealing with large time series data sets (Big Data)
  • Proven track record of developing and applying statistical, probabilistic and machine learning technologies to complex systems
  • Creative and innovative mindset
  • Strong analytical and problem solving skills
  • Proven leadership ability
  • Strong ability to communicate analytical results with design engineers, business leaders, and other stakeholders, highlighting actionable insights
#DTR