Principal Data Scientist/Modeler
- Full-Time
- Baltimore, MD
- Exelon Corporation
- Posted 3 years ago – Accepting applications
Job Description
Description
At Exelon, we've got a place for you!Join the nation's leading competitive energy provider, with one of the largest electricity generation portfolios and retail customer bases in the country. You will be part of a family of companies that strives for the highest standards of power generation, competitive energy sales, and energy delivery. Our team of outstanding professionals is focused on performance, thought leadership, innovation, and the power of ideas that come from a diverse and inclusive workforce.
Exelon will provide you the tools and resources you need to design, build and enhance a successful career. We are also dedicated to motivating the success of our employees through competitive base salary, incentives, and health and retirement benefits.
Join Exelon and share your passion at a forward-thinking Fortune 100 company. Establish yourself in a place where you can truly shine and create a brighter, more sustainable tomorrow. Energize your career at Exelon!
PRIMARY PURPOSE OF JOB
The Principal Data Scientist/Modeler will report to the Senior Manager, Genco Strategy as part of a data science team, and will utilize their analytical, statistical and programming skills to develop new data-driven solutions to a broad range of use cases related to retail and wholesale business areas. Data scientist will apply machine learning, deep learning, and Natural Language Processing methods to improve and optimize customer experience, drive efficiencies, and other positive business outcomes. A wide range of technical competencies and subject matter expertise will be leveraged, including statistics, machine learning, artificial intelligence, feature engineering, data mining, ETL, coding languages (Python, R, Scala) and databases (SQL). The data scientist will work closely with other Data Scientists ,Machine Learning Engineer, business stakeholders and senior leadership to identify use cases and develop custom machine learning models, as well as share knowledge with team members and IT partners to support the growth and development of machine learning at Exelon.
PRIMARY DUTIES AND ACCOUNTABILITIES
- Building and cleaning data, leveraging data gathering techniques and assessing the effectiveness and accuracy of new data sources
- Modeling/Algorithm development
- Collaboration with business stakeholders, IT, ML Engineer and leadership
- Maintain and improve models over time for accuracy and additional features; develop processes and tools to monitor and analyze model performance and data accuracy
Qualifications
MINIMUM QUALIFICATIONS- Advanced Degree or PhD in statistics, mathematics, computer science, data science or another quantitative field
- 8+ years of experience manipulating data sets and building statistical models
- Experience with feature engineering, augmenting data, and advanced signal processing
- Experience using programming languages to manipulate and draw insights from large data sets
- Knowledge and real-world business applications of Machine learning models (Classification, clustering, decision tree learning, artificial neural networks, regression etc.)
- Knowledge and real-world business applications of advanced statistical techniques and concepts (regression, distributions, statistical test and proper usage, etc.)
- Excellent written and verbal communication skills
- A drive to learn and master new technologies and techniques
- Demonstrated ability with cloud infrastructures such as IBM, Azure, AWS
- Strong problem solving skills
PREFERRED QUALIFICATIONS
- Experience constructing Machine Learning pipelines in Databricks & Apache Spark
- Understanding of container and orchestrator technologies like Docker & Kubernetes
- Experience using neural network frameworks such as, Tensorflow & PyTorch
Exelon is proud to be an equal opportunity employer and employees or applicants will receive consideration for employment without regard to: age, color, disability, gender, national origin, race, religion, sexual orientation, gender identity, protected veteran status, or any other classification protected by federal, state, or local law.
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