Data Science Mgr & Head-Grid T&D, Safety - Exelon

Job Description

Description

Be a part of something powerful at America's premier energy provider!

At Exelon, we are 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 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 empowered to evolve and advance our careers in an open and inclusive environment. We pride ourselves on being the kind of place where people want to come and stay. We know that investing in our employees' futures strengthens ours, which is why we offer competitive compensation, incentives and health and retirement benefits.
 

PRIMARY PURPOSE OF POSITION
 

• Lead ongoing delivery and deployment of analytics-driven products by applying 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).

• Train state of the art algorithmic models, including but not limited to tree-based approaches and neural networks, and implement those models into a production environment following the established MLOps approaches.

• 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. 

• Possess deep knowledge of underlying technologies across the full data science lifecycle, and their interplay. In addition, is an expert developer in Python and its data stack and is able to match tasks to the appropriate toolset.

• 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.

• Supervise and lead a diverse team of 6-10 direct reports and/ or contracted labor, as well as strategic partners across Exelon. Mentor junior peers and oversee their activities where needed.  Provide subject matter expertise in the areas of artificial intelligence, machine learning, feature engineering, 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

            1          Develop key predictive models that lead to delivering a premier customer experience, operating performance improvement, and increased safety best practices. Supervise and lead a diverse team of 6-10 direct/ in-direct reports and/ or contracted labor, as well as strategic partners across Exelon. Provide accurate and timely feedback regarding performance

            2          Develop and maintain an environment that fosters a high-performance culture and learning. Analyze data using advanced analytics techniques in support of process improvement efforts using modern analytics frameworks, on-prem or cloud, including but not limited to: Python, R, Scala, or equivalent; Spark/PySpark; Hadoop file system; GPU-based computing systems

            3          Access and analyze data sourced from various Company systems of record. Lead the development of strategic business, marketing, and program implementation plans.

            4          Access and enrich data warehouses across multiple Company departments. Build, modify, monitor and maintain high-performance computing systems.

            5          Provide expert data and analytics support to multiple business units. Provide guidance and be a mentor to  junior peers.

            6          Represent the Company at analytics focused industry forums and peer group events, bringing back leading practices to evolve the Company’s analytics maturity.

POSITION 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.

• Manager/ lead a diverse team of 6-10 direct or indirect reports and/ or contracted labor, as well as strategic partners across Exelon. 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.

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 managing people and delivering projects on time. Ability to build consensus, establish trust, communicate effectively and foster culture change.

Analytical Abilities:

Demonstratable strong knowledge in the areas of machine learning, artificial intelligence, and statistical modeling, including boosted decision trees, deep neural networks, timeseries forecasts, etc., data mining, data visualization and the keen ability to select the appropriate method for the task at hand.

Technical Knowledge:

• Proven experience in analytics/statistics/visualization platform of choice, but preferably in the MS Azure suite as well as  Python, SQL.

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:

PhD from a leading program in a Quantitative discipline.

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

Experience:

• Prior professional experience in the utilities or broader energy sector.

• Prior exposure to data structures pertaining to smart-meters, billing, or outage management systems.

• Demonstratable strong knowledge around the full spectrum of data science lifecycle, including analytics-driven product delivery.

Analytic Abilities:

Superior understanding of relevant theories in machine learning, statistics, probability theory, data structures and algorithms, optimization, etc.,p>
Technical Knowledge:

• Ninja level coding skills (Python, R, Scala, etc) developing in a Unix environment.

• Expert knowledge of git, MLOps principles, and distributed compute platforms

• Proficiency in database management: create, edit, update, join, append and query data from columnar and big data platforms.

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:

Strong experience managing people, and ability to build consensus, establish trust, communicate effectively and foster culture change