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Data Scientist (Electric Transmission Network Modeling Specialization)

datasocietyRichmond, Virginia, United StatesOnsite
This job is no longer open

We Are:


At Data Society Group, we provide the highest quality, leading-edge, industry-tailored data and AI training and solutions for Fortune 1,000 companies and federal, state, and local governmental organizations. We partner with our clients to educate, equip, and empower their workforces with the skills they need to achieve their goals and expand their impact. Data Society Group publishes CDO Magazine, the preeminent global publication for Data Officers. Our executive boards include industry leaders, engineers, and data scientists from across the world.

We are empowering the workforces of the future, from data literacy for all employees to support for data engineers and data scientists to train up on the most complex AI solutions and Machine Learning skills.

The Role:


The Data Scientist is responsible for overseeing the collection, analysis, and interpretation of data. Their duties include sifting through data to create organized categories, comparing data to current processes specific to power grid systems, and creating reports outlining business predictions. The Data Scientist will support data-centric consulting projects specific to forecast modeling, working with traditional Data Science tools such as R or Python, and tools specific to Electric Transmission Planning and Modeling such as the Siemens PSS®E tool.

Work experience in Python, data analysis, and transmission network planning is required. Experience working for a utility or power company is strongly preferred for this role.

Responsibilities:


● Support Transmission modeling planning projects; work with client teams to understand the implication of proposals for new supply and load projects; assist in the communications with partner organizations regarding modeling design and results.● Research and devise innovative forecasting methods for short-term and long-term predictions.● Extract, transform, and load data using a variety of data formats.● Conduct new research, identify, and incorporate new data sources as needed to create comprehensive data streams.● Create reports and presentations for business use cases.● Correlate results with actionable insights.● Communicate findings and present them to business stakeholders and subject matter experts, utilizing the skill to communicate complex concepts in a simple way.● Keep current with technical, economic, and industry developments.● Collaborate with product design and engineering teams to develop an understanding of reporting needs.

Implement analytical models in production by collaborating with software developers and machine-learning engineers.

Skills You Bring:


● Five or more years of experience in data analysis, with knowledge of different forecast modeling techniques.● Experience using Transmission Network Modeling tools including but not limited to Siemens PSS®E or PROMOD.● Advanced degree in data science, computer science, mathematics, statistics, or engineering or a similar field of study.● Proficiency with data mining, mathematics, statistical analysis, machine learning.● Advanced experience in pattern recognition and predictive modeling.● Experience working with databases and ability to extract and manipulate data using at least one of SQL variants.● Experience with programming languages (e.g., Python, R).● Experience with data visualization tools (e.g., PowerBI, Tableau).● Experience with version control tools such as Git and version control platforms (e.g., GitHub, Bitbucket or Azure DevOps).● Ability to work effectively in a dynamic, research-oriented group that has several concurrent projects.● Exceptional technical writing skills.● Work experience in Python, data analysis, and forecasting is required.● Due to the nature of work performed, U.S.

citizenship is strongly preferred, as is the ability to obtain a Public Trust clearance.The ideal candidate is local to the Richmond, VA or Washington, DC metro area and able to meet criminal history and citizenship requirements for federal contracts. In addition to that, the ideal candidate is to demonstrate education or experience in Python, data analysis, and forecast modeling. Current salary range is $110,000-$120,000 though we are open to negotiation. This position is eligible for full benefits including health, medical, dental, short and long-term disability, and life insurance, as well as our 401k, transit subsidy, unlimited PTO, and 15 paid holidays during 2024.

Affirmative Action Statement


At Data Society, we don't just accept differences - we celebrate them, we support it, and we thrive on it for the benefit of our employees, our products, and our community. Data Society is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunities regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements.

If you have a disability or special need that requires accommodation, please let us know.

We do not accept unsolicited resumes from third party recruiters.



This job is no longer open

Life at datasociety

Thrive Here & What We Value- Remote-friendly organization- Celebrate differences and support it for the benefit of employees, products, and community- Equal opportunity workplace and affirmative action employer- Committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status- Accommodation for disabilities- Flexible work arrangements with preference for candidates in the metro Richmond, VA or Washington, DC areas- Competitive salary and benefits package including Unlimited PTO, Healthcare Insurance, 401k, Metro Transit subsidy, Paid Parental Leave, and Paid Disability – all on Day 1
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