AES is looking for data scientists to join our growing team of data wranglers that will help us uncover insights and drive key business decisions by leveraging data analytics and artificial intelligence. The data scientist will use data to find patterns, create algorithms and generally help AES’ business leaders make smarter decisions to deliver better products and solutions. The analytics will also serve as the foundation for machine learning use cases across several business applications. The primary use cases will be in applying data mining techniques, performing statistical analysis to improve asset reliability across our green generation portfolio, make our energy grids more resilient and able to cope with tomorrows renewable demands and drive operational efficiencies for our commercial teams. Help us accelerate our greener energy future using data and application of analytics!
- Selecting features, building and optimizing classifiers using machine learning techniques
- Data mining using state-of-the-art methods
- Visualizing data to provide predictive insights and drive decision making
- Extending company’s data with third party sources of information when needed
- Enhancing data collection procedures to include information that is relevant for building analytic systems
- Processing, cleansing, and verifying the integrity of data used for analysis
- Performing ad-hoc analyses and presenting results and business outcomes in a clear and compelling manner
- Creating automated anomaly detection systems and constant tracking of its performance
- Be an evangelist for the use and data and data driven decision making at all levels of the organization
Skills and Qualifications
- Bachelors in Engineering, Mathematics, Physics applicable real-world experience required, Masters or Phd. preferred.
- 3+ years’ experience in data analytics or data science or applicable research
- Excellent understanding of machine learning techniques and algorithms, such as k-NN, Naive Bayes, SVM, Decision Forests, etc.
- Experience in the production of energy, commercial energy markets or energy industry preferred
- Experience with common data science toolkits, such as R, Python, SAS, NumPy, MatLab, etc. Deep experience in Python or R is highly desirable
- Experience using cloud platforms (Azure ML, GCP ML, AWS SageMaker) and deploying analytics in a production environment (Microsoft Preferred)
- Demonstrates natural curiosity, an ability and willingness to challenge assumptions and gain a deeper understanding of the problem leveraging contextual inquiry
- Takes ownership, promotes perspectives and insights in a way that gives others comfort about how they were derived and what the next natural questions might be
- Excellent communication and collaboration skills to ensure analytics projects are meeting the needs of the business users
Proficiency in using query languages such as SQL, Hive, Pig
- Experience with NoSQL databases, such as MongoDB, Cassandra, HBase
- Strong applied analytics and statistics skills, such as distributions, statistical testing, regression, etc.
- Demonstrated ability to develop and deploy scripts and programming skills
- Data-oriented personality