Manager Data Science (Hybrid)

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.

This position is part of the BGE’s Advanced Data Science and Intelligence Group (ADSI). The successful candidate will lead a group of data scientists, quantitative engineers, and other data specialists. This group’s mission is to help BGE evolve into an analytics powerhouse by utilizing data to derive meaningful insights and provide actionable intelligence. The successful candidate will be responsible for integrating data-driven decision-making into the BGE culture and expanding the use of Advanced Analytics within the company. In this role, you’ll advocate for our data-driven culture, leading a team of analysts while also directly contributing to conducting analysis and providing strategic recommendations.

Responsibilities include but are not limited to:

• Coordinate project teams of data scientists and supporting roles, acting as the primary point of contact in delivering end-to-end innovative, high-quality data solutions with measurable business value and customer value.
• Build relationships with partner teams, frame and structure questions, as well as summarize and present key insights to both technical and non-technical audiences
• Partner with cross-functional teams of quantitative engineers, leaders, and product owners to deliver a product that stakeholders want and can use
• Enable all organizations to adopt data analytics by providing strategic direction, education, tools, and resources.
• Utilize data to provide meaningful and actionable insights, thus, allowing for more informed decision-making company-wide
• Enhance current processes and decision-making through descriptive, predictive, and prescriptive analytics.
• Develop a high-level understanding of cutting-edge data science tools and techniques
• Build machine learning models through all phases of development, from design through training, evaluation, validation, and implementation
• See the projects through the entire data science lifecycle, from problem definition to data exploration, data munging, modeling, analysis, and deployment into production systems.
• Assist management in the recruiting process in order to build a high-functioning Data Science team
• Coach, mentor, and guide data science SMEs to advance their career development in both technical and non-technical areas

Looking for someone who has the following skillset/experience:

• Experience in building small data science teams and scaling
• Any experience in electric or gas utility, customer operations, or any other related areas is a plus
• Experience in translating complex business needs/cases, breaking into actionable stages, and delivering 
• Hands-on experience developing data science solutions using open-source tools and cloud computing platforms
• Experience with clustering, classification, sentiment analysis, time series, and deep learning
• Experience in developing a project plan including milestones, dates, owners, and risks and contingency plans
• Knowledge and understanding of enhanced Project Management techniques such as Agile and/or Scrum. 
• Experience in Telematics, Internet of Things – IoT, and/or Sensor Data

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. Supervise and lead a diverse team of 4-6 direct reports and/or contracted labor, as well as strategic partners across Exelon. Provide accurate and timely feedback regarding performance. (35%)
• 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, including but limited to: Python, R, Scala, or equivalent; Spark/PySpark; Hadoop file system; GPU-based computing systems (20%)
• Provide expert data and analytics support to multiple business units. Provide guidance and be a mentor to junior peers. (20%)
• Access and enrich data warehouses across multiple Company departments. Build, modify, monitor and maintain high-performance computing systems. (10%)
• Access and analyze data sourced from various Company systems of record. Lead the development of strategic business, marketing, and program implementation plans. (10%)
• Represent the Company at analytics focused industry forums and peer group events, bringing back leading practices to evolve the Company's analytics maturity. (5%)

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.
• Manage/ Lead team of up to 4-6 indirect or indirect employees and consultants. Become a trusted mentor to peers and collaborators.
• 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

• 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: Demonstrable 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.

• Education: Masters, or PhD from a leading program in a Quantitative discipline.
• 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. Demonstrable 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.
• Technical Knowledge: Ninja level coding skills (Python, R, Scala, etc) developing in a Unix environment. 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.