Prin Data Scientist

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 for coverage during storms or other energy delivery emergencies.

Note: This is a hybrid position (in-office with remote flexibility). Employees are required to be in office at least three days per week (Tuesday, Wednesday, and Thursday). This position must sit out of our Philadelphia -PA, Newark - DE, Washington -DC, Oakbrook Terrace - IL, Baltimore - MD or Newark - DE office.  This position is not eligible for relocation assistance.

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. 

PREFERRED QUALIFICATIONS

• Education: Masters, or PhD from a leading program in a Quantitative discipline. 
• Experience: Prior professional experience in the utilities or broader energy sector. In-depth familiarity with industry-specific data domains—including geospatial/GIS layers, remote sensing and imagery, AMI/MDMS billing data, real-time SCADA/telemetry feeds, outage or distribution management systems (OMS/DMS), work management and asset management datasets. 
• Analytic Abilities: Superior understanding of relevant theories in machine learning, deep learning, generative AI, statistics, probability theory, data structures and algorithms, optimization, etc. 
• 5+ years of experience with Python and SQL. Proficiency in database management: create, edit, update, join, append and query data from columnar and big data platforms.  
• 5+ years of experience designing, building, deploying, and operating secure, cost-efficient end-to-end ML solutions on Microsoft Azure, covering Spark/Delta feature pipelines, MLflow-tracked experimentation, distributed training, registry-based model governance, automated CI/CD, real-time/batch serving, and monitoring. 
• 2+ years of experience developing with Azure AI stack (AI Foundry, Open AI + AI Search), LLM orchestration framework (e.g., langchain, promptflow, llamaindex) 
• Communication Skills: Ability to clearly translate executive and analytics leaders’ vision and guidance into methods and analytics. Strong time management and presentation skills. 
• Leadership Skills: Experience leading technical teams, and ability to build consensus, establish trust, communicate effectively and foster culture change