Sr Data Scientist

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. 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. This requires understanding business needs, providing and receiving regular feedback, and planning the proper transfer of developed solutions. Mine big and small data for insights, using advanced statistic and machine learning methods. 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. Share knowledge with team members, and business stakeholders, and IT partners. 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.

Position may be required to work extended hours for coverage during storms or other energy delivery emergencies.

• Develop key predictive models that lead to delivering a premier customer experience, operating performance improvement, and increased safety best practices. Develop and recommend data sampling techniques, data collections, and data cleaning specifications and approaches. Apply missing data treatments as needed.
• 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. Support 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
• Works with stakeholders and subject matter experts to understand business needs, goals and objectives. Work closely with business, engineering, and technology teams to develop solution to data-intensive business problems and translates them into data science projects. Collaborate with other analytic teams across Exelon on big data analytics techniques and tools to improve analytical capabilities.

• Support business unit strategic planning while providing a strategic view on machine learning technologies.
• Advice and counsel key stakeholders on machine learning findings and recommend courses of action that redirect resources to improve operational performance or assist with overall emerging business issues.
• Provide key stakeholders with machine learning analyses that best positions the company going forward.
• Educate key stakeholders on the organizations advance analytics capabilities through internal presentations, training workshops, and publications.

• Bachelor's degree in a Quantitative discipline. Ex: Applied Mathematics, Computer Science, Finance, Operations Research, Physics, Statistics, or related field
• 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.
• 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.

• Masters, or PhD in a Quantitative discipline. Ex Applied Mathematics, Computer Science, Finance, Ops Research, Physics, Statistics, or related field
• Prior exposure to time series, graph 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, prior professional experience in utilities.
• Experience tailoring advanced analytics tools tuning the ML models for specific requirements, as well as ability to test, record and communicate impact.
• 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 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.
• Ability to translate executive and analytics leaders' vision and guidance into methods and analytics. Strong time management and presentation skills.
• 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 for planned uses usecases.
• Demonstrated experience with time series classification, regression, and other applied statistics methods, remote sensing data science experience, container development and production on prem and cloud data pipelines support, ML and cloud engineering, graph databases and experience with systems like data bricks, high performance unix compute is a plus.
• Work will include building advanced graph neural network models, higher dimensional graph modeling, remote sensing satellite aerial lidar drone image analytics

• Annual salary will vary based on a candidate's skills, qualifications, experience, and other factors:USD $104,000.00/Yr. - USD $156,000.00/Yr.
• Annual Bonus for eligible positions: 15%
• 401(k) match and annual company contribution
• Medical, Dental and Vision Insurance
• Life and disability insurance
• Generous paid time off options, including vacation, sick time, floating and fixed holidays, maternity leave and bonding/primary caregiver leave or parental leave (based on position)
• Long Term Incentive Plan for eligible positions
• Wellbeing programs such as tuition reimbursement, adoption assistance and fitness reimbursement
• Referral bonus program
• And much more

• Develop key predictive models that lead to delivering a premier customer experience, operating performance improvement, and increased safety best practices. Develop and recommend data sampling techniques, data collections, and data cleaning specifications and approaches. Apply missing data treatments as needed.
• 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. Support 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
• Works with stakeholders and subject matter experts to understand business needs, goals and objectives. Work closely with business, engineering, and technology teams to develop solution to data-intensive business problems and translates them into data science projects. Collaborate with other analytic teams across Exelon on big data analytics techniques and tools to improve analytical capabilities.

• Bachelor's degree in a Quantitative discipline. Ex: Applied Mathematics, Computer Science, Finance, Operations Research, Physics, Statistics, or related field
• 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.
• 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.