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ComEd - Principal Data Scientist - Oakbrook Terrace, IL
Job Description
Description
Be a part of something powerful at America's leading energy provider!
At Exelon, our people are the heart and soul of our business. Whether it's powering lives, supporting communities or collaborating with colleagues, an Exelon employee is talented, compassionate, forward-thinking and inspired. We are a Fortune 200 company united by our values and shared vision for a cleaner and brighter future. We encourage curiosity, value diverse perspectives and we never stop looking for ways to be, work and do better. We know the future is in our hands. That's why we're looking for people like you, who have the power to make a difference.
As the nation's largest utility company, we serve more than 10 million customers through six fully regulated transmission and distribution utilities -- Atlantic City Electric (ACE), Baltimore Gas and Electric (BGE), Commonwealth Edison (ComEd), Delmarva Power & Light (DPL), PECO Energy Company (PECO), and Potomac Electric Power Company (Pepco). All 18,000 of us are committed to delivering safe, reliable and affordable energy to our customers, strengthening our communities, supporting a clean energy future and reducing our impact on the changing climate.
Our people are empowered to evolve and advance their careers in an open and inclusive environment. We pride ourselves on being the kind of place where people want to come, stay and grow -- whether that's in the role and path they start in or in new and exciting career opportunities across our business. We know that investing in our employees' futures strengthens ours, which is why we offer competitive compensation, incentives, opportunities for career path changes, and health and retirement benefits.
PRIMARY PURPOSE OF POSITION
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. Leverage these insights to deploy data-driven applications in support of strategic business priorities. Possess an advanced knowledge of predictive modeling techniques, and prior exposure with high-performance computing technologies. Use your skills to manage several projects running in parallel. Closely collaborate with various internal stakeholder and external partners to understand business needs, by providing and receiving regular feedback. Use these collaborations to plan, execute, and deploy analytics-based solutions. Mentor to more junior peers and oversee their activities where needed. Provide subject matter expertise in the areas of artificial intelligence, machine learning, feature engineering, data mining, data manipulation/storage, and high-performance computing. A successful candidate will quickly adopt the team's established working processes and toolkit while growing his/her knowledge of the utilities industry.
Position may be required to work extended hours, including 24 x 7 coverage during storms or other energy delivery emergencies.
PRIMARY DUTIES AND ACCOUNTABILITIES
- 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 limited to: Python, R, Scala, or equivalent; Spark/PySpark; Hadoop file system; GPU-based computing systems.
- Access and analyze data sourced from various Company systems of record. Lead the development of strategic business, marketing, and program implementation plans.
- Access and enrich data warehouses across multiple Company departments. Build, modify, monitor and maintain high-performance computing systems.
- Provide expert data and analytics support to multiple business units. Provide guidance and be a mentor to junior peers.
- Represent the Company at analytics focused industry forums and peer group events, bringing back leading practices to evolve the Company's analytics maturity.
JOB SCOPE
- Research and experiment on data science technologies, discover opportunities for new data analytics features, and influence product and technology strategies of the company.
- Develop algorithms (machine learning, statistical modeling, optimization) that power data analytics solutions.
- Drive the productization of the algorithms either by writing high-quality, reusable code modules or advising the engineering teams on implementing the algorithms.
- Communicate research results effectively in written and spoken forms to various audiences including product managers, system engineers, business executives, and customers.
- Become a trusted mentor to peers and collaborators.
- Educate the organization on data science technologies and data analytics through internal presentations, training workshops, and publications.
- Represent the organization and advocate its data analytics efforts and capabilities through external conferences and publication opportunities.
*The position includes impact opportunities in three main directions - investment optimization, operations process improvements and new technologies research (e.g. adversarial graph neural networks as applied to utility space). The Principal Data Scientist will apply the scientific method to extract knowledge and insights from data, which may take the form of time-series, structured and unstructured data sets. They will leverage these insights to deploy data-driven applications in support of strategi business priorities. This includes, for instance, applying advanced machine learning (ML) and high-performance computation methods to diverse types of data sets (time series, images, radar, LiDAR, weather related data, human created reports, etc.) The Principal Data Scientist will constantly be in the process of discovery of impactful business problems that can be solved with state-of-the-art tools, techniques and technology given the available data. Most crucially, they will research core causes which determine influential parameters and associated data sources, leading to appropriate model selection. This will determine the mathematical transformations to be applied to the data while creating features for ML training. The position demands intricate understanding of model performance optimization to the unique business needs specific to electric utilities and in a rapidly changing environment.
Qualifications
MINIMUM QUALIFICATIONS
- Education: Bachelor's degree in a Quantitative discipline. Ex: Applied Mathematics, Computer Science, Finance, Operations Research, Physics, Statistics, or related field
- Experience: Minimum of 8 years of experience analyzing multi-terabyte datasets. Minimum of 3 years of experience applying advanced analytics techniques to diverse data sets data. Minimum of 3 years of experience in data mining in a business environment with large, complex datasets. Minimum of 2 years of experience in a supervisory role, including mentoring and guiding junior peers, responsible to successfully delivering projects on time.
- Analytical Abilities: Demonstratable strong knowledge in the following areas: machine learning, artificial intelligence, statistical modeling, data mining, information retrieval, or data visualization.
- Technical Knowledge: 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.
- Communication Skills: Ability to translate data analysis and findings into coherent conclusions and actionable recommendations to business partners, practice leaders, and executives. Strong oral and written communication skills. Experience presenting to diverse audiences including presenting to conferences and business symposia.
PREFERRED QUALIFICATIONS
- Education: Masters, or PhD from a leading program in a Quantitative discipline.
- Experience: Prior professional experience in the utilities. Prior exposure to time series, graph and tabular data structures. Understanding for mathematical/quantitative description methods and modeling approaches for phenomena in engineering and physics in general, ability to choose the correct approach for a given situation, data availability and quality.
- Background in electrical engineering, physics, mathematics, or related disciplines.
- Experience tailoring advanced analytics tools/tuning the ML models for specific business requirements, as well as ability to test, record and communicate impact.
- Analytic Abilities: Data intuition, curiosity and drive to dive deep into data and discussion with SME's, understand phenomena, leading root cause analysis.
- Mathematical/statistical modeling for diverse phenomena, revealing influential variables, creating features from the existing data, proper data cleaning and structuring of training data tables, discovery of confounding variables and data leaks, statistical model training, testing and tuning.
- Exceptional understanding of fundamentals and relevant theories (including probability theory, statistics, data structures, and algorithms, machine learning, optimization, etc.) as well as being current on recent developments.
- Technical Knowledge: Transformer ML models, graph networks and graph neural networks, advanced modeling for timeseries forecasting, deep technical understanding of modeling and engineering/physics specific feature development, computational optimization for large scale computations. Data structures, high volume and speed data access, storage and database optimization, sharding and table structure optimization for planned uses/usecases.
- Communication Skills: Ability to clearly and eloquently communicate (orally and in writing) how analytics leaders' vision critically contributes to and underpins company strategy to a variety of internal and external stakeholders including executives and community representatives. Strong track record of preferably academic publications.
- Leadership Skills: Ability to build consensus, establish trust, communicate effectively and foster culture change
- Technical Skills: Demonstrated mastery of tools of the craft (some current examples: Python, SQL, any ML toolbox/toolset e.g. sklearn, tensorflow, torch, etc...). Strong fundamentals in data science (probability theory, applied statistics, core machine learning algorithms, basics of data structures, databases and high-performance computing). Demonstrated advanced knowledge and experience with predictive modeling techniques on a variety of data types including time series, graphs and strong demonstrated ability high-performance computing technologies.