Exelon is looking to extract knowledge and insights from various data sets to inform decision making and drive solutions for a cleaner, brighter future in the energy sector.
Requirements
- 4-7 years of relevant experience developing hypotheses, applying machine learning algorithms, validating results to analyze multi-terabyte datasets and extracting actionable insights is required.
- Previous research or professional experience applying advanced analytic techniques to large, complex datasets.
- Strong knowledge in at least two of the following areas: machine learning, artificial intelligence, statistical modeling, data mining, information retrieval, or data visualization.
- Proven experience in developing and deploying predictive analytics projects using one or more leading languages (Python, R, Scala, etc.).
- Experience working within an open source environment and Unix-based OS.
- Expert level coding skills (Python, R, Scala, SQL, etc), and experience developing in a Unix environment.
- Proficiency in database management and large datasets: create, edit, update, join, append and query data from columnar and big data platforms.
Responsibilities
- Apply the scientific method to extract knowledge and insights from data, which may take the form of time-series (smart-meters, smart-grid, and other IoT), structured (relational data stores), and unstructured (text and multi-media) data sets.
- Mine big and small data for insights, using advanced statistic and machine learning methods.
- Collect, cleanse, standardize and analyze data from a variety of internal and external sources.
- Produce novel insights to help inform business actions using statistical modeling and machine learning techniques on complex data-sets on the order of several terabytes or petabytes.
- Develop key predictive models that lead to delivering a premier customer experience, operating performance improvement, and increased safety best practices.
- Analyze data using advanced analytics techniques in support of process improvement efforts using modern analytics frameworks, including, but not limited to; Python, R, Scala or equivalent, Spark, Hadoop file system and others
- Access and analyze data sourced from various Company systems of record.
Other
- Closely collaborate with various internal stakeholders, information architects, data engineers, project/program managers, and other teams to turn data into critical information to inform decision making.
- Understanding business needs, providing and receiving regular feedback, and planning the proper transfer of developed solutions.
- Validate findings with the business by sharing analysis outputs in a way that can be understood by business stakeholders.
- Become a subject matter expert in the areas of artificial intelligence, machine learning, feature engineering, data mining, and data manipulation/storage.
- Demonstrate commitment to continuous learning and professional development in technical subject matter.
