Principal Data Scientist

Fox Valley Facility, Illinois, US
Apr 28, 2021
May 11, 2021
Climate Change
Employment Type
Full time
Salary Type
We are building a true top tier analytics group - a small, nimble, autonomous team of cross functional specialists.

Goal is simple - do maximum good - have a true impact TODAY (climate change, aging infrastructure, limited human and monetary resources, other calamities are challenging the granted persistence of a fundamental pillar of our edification - always on electricity).

Method - anything goes (continuously improving Tools, Techniques, Technology). Long term plan - build a (true) AI into the distribution grid (decentralized - estimated 700 trillion - not billion - rows of data processed on the edge).

Reason - self monitoring (interconnected - IOT, AMI, PMU, oscillography, drones, satellite images, lidar, weather radar like NEXRAD, human generated reports, etc...), self-healing (DA devices, relays, automated alerts, AI requested repairs and inspections, rerouted current, lowered voltage, etc...) - a true "hive mind" with different "species" of IOT incorporating the mass collected information into the huge number of decisions the "hive" will be executing on.

Apply the scientific method to extract knowledge and insights from data, which may take the form of time-series (smart-meters, smart-grid, weather 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.


Develop key predictive models improving grid reliability and resiliency, improving grid response to severe weather events as well as gray sky day and long term climate change effects, 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, or equivalent; ArcGIS or equivalent, weather data collection and analysis systems

Access and analyze data sourced from various Company systems of record. Lead the development of strategic business, resiliency, weather impact reduction, 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


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

Minimum of 8 years of experience analyzing 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.

Analytical Abilities:
Demonstratable 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 or Climate related 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.

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.

Strong understanding of weather-related data, collection and analysis, impact of climate on grid, preferably with machine learning modeling experience in that discipline.

Technical Knowledge: Strong coding skills (Python, R, Scala, etc).

Proficiency in working with various databases and data storage systems.

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

Strong time management and presentation skills. Strong track record of (academic preferably) publications.

Leadership Skills:

Ability to build consensus, establish trust, communicate effectively and foster culture change.

Research and experiment on data science technologies, discover opportunities for new data analytics features, and influence resiliency planning, investment 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.
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.

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