Data Scientist for Energy, Environment & Utilities Industry

Key Skills

AWS, Azure, Cloudera, Data Analytics, Design of Experiment, IBM Cognos, Java Programming, Mathematics, Predictive analytics, Python Programming, R Programming, Scala Programming, SPARK Programming, SQL, Statistics

Job Description

As a Data Scientist at IBM, you will help transform our clients’ data into tangible business value by analyzing information, communicating outcomes and collaborating on product development. Work with Best in Class open source and visual tools, along with the most flexible and scalable deployment options. Whether it’s investigating patient trends or weather patterns, you will work to solve real world problems for the industries transforming how we live.

Your Role and Responsibilities
You will be responsible for successful delivery of data science solutions and services to IBM EE&U clients; experience in predictive modeling, optimization, and/or machine learning analytics techniques using tools/programming languages including R, Python, Spark, etc. within a Hadoop-enabled environment. Define key business problems to be solved; formulate mathematical approaches and gather data to solve those problems, develop, analyze/draw conclusions, test solutions and present to client. Enhance performance by applying advanced mathematical modeling, data analytics, optimization, and machine learning techniques. The key success metric for this role is productive utilization but the candidate will support the Communication Sector leader with business development and pipeline growth as needed.
The ideal candidate will possess the following skillsets:

• You’re great at solving problems by looking at thing differently, debugging, troubleshooting, and designing & implementing solutions to complex technical issues.
• You thrive on teamwork and have excellent verbal and written communication skills.
• Strong fundamentals in Mathematics and Computer Science (algorithms)
• You have strong technical and analytical abilities, a knack for driving impact and growth, and some experience with programming/scripting in a language such as Java or Python.
• You’re proficient at least one of the statistical programming language such as R, Python, or Scala
• You have an interest in, understanding of, or experience with Design Thinking and Agile Development Methodologies
• You have a basic understanding of Cloud (IBM Cloud, AWS, Azure, etc)

You have a basic understanding of how energy and utilities operate, as well as the analytical use cases and applications that are driven by weather and climate intelligence.

Required Technical and Professional Expertise
Candidates must have 2-3+ years experience in the following:

• Proficiency reading and writing Python code and using Open Source Python packages / models
• Proficiency in at least one or more of the major Cloud platforms including IBM Cloud, AWS, and/or Azure
• Proficiency in at least three or more of the following energy and weather analytics use cases:
  • Load/demand forecasting
  • Renewables forecasting
  • Energy trading
  • Outage prediction/resource optimization
  • Vegetation management
  • Asset inspection/detection/correction
  • Asset failure analysis
  • Predictive maintenance
  • Dynamic Line Rating (DLR) prediction
  • Weather forecasting and analysis
  • Field worker safety/alerting
  • Climate risk analytics
  • Weather data warehouse/lake
  • Weather data integration
• Practical experience with data analytics, predictive analytics, mathematics, statistics, or similar field
• Practical experience developing predictive or statistical models such as regressions, decision trees, neural networks, simulations, and/or optimizations
• Consulting and or client facing experience

Candidates must have 1-2+ years experience in the following:

• Geospatial analytics and the use of GIS applications such as QGIS and ESRI/ArcGIS
• Computer vision/image detection analytics
• Familiarity with downloading and analyzing satellite imagery and/or LiDAR data
• Familiarity with downloading and analyzing weather data (historical, current, and forecasted)
• Ability to query data using APIs

Preferred Technical and Professional Expertise

• Master’s degree in Engineering, Computer Science, Data Science, or Business Analytics
• Familiarity with asset management systems such as Maximo
• Experience with deep learning technologies such as TensorFlow
• Multi-lingual a plus