Principal Data Scientist

Primary Duties and Accountabilities
Develop key predictive models that lead to delivering performance improvement and optimize specific performance criteria. 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 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 solutions to data-intensive business problems and translate them into data science projects. Collaborate with other analytic teams across Exelon on big data analytics techniques and tools to improve analytical capabilities.

Minimum Qualifications
Education: Bachelor's degree in a Quantitative discipline. Ex: Data Science, Data Analytics, Applied Mathematics, Statistics, Computer Science, Operations Research, or related field

Experience: Over 10 years of relevant experience developing hypotheses, applying machine learning algorithms, validating results to analyze large datasets and extract actionable insights is required. Previous research or professional experience applying advanced analytic techniques to large, complex datasets.

Analytical Abilities: Strong knowledge in at least two of 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.).

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.

Preferred Qualifications
Education: Masters, or PhD in a Quantitative discipline.
Experience: Prior exposure to the full spectrum of data science lifecycle, including data acquisition, maintenance, processing, analysis, and communication.

Analytic Abilities: Solid understanding of relevant theories in machine learning,statistics, probability theory, data structures and algorithms, optimization, etc.

Technical Knowledge: Expert level coding skills (Python, R, Scala, SQL, etc)
Proficiency in database management and large datasets: create, edit, update, join, append and query data from columnar and big data platforms.

Communication Skills: Ability to translate executive and analytics leaders' vision and guidance into methods and analytics. Strong time management and

presentation skills