Energy Data Analyst

Posted 2 Days Ago
Pittsburgh, PA, USA
In-Office
Mid level
Analytics • Energy
The Role
Analyze large energy datasets to answer research questions, evaluate wholesale electricity market dynamics, measure product performance, and provide statistical-backed insights to improve models and products while collaborating with data science teams.
Summary Generated by Built In
Company Description

kWantera is a venture-backed startup company dedicated to helping companies manage their energy. Our team of quantitative energy market analysts work with our big data analytics platform to analyze and react to changing market conditions. At kWantera, we promote a highly dedicated, collaborative and creative work environment where our employees take ownership of their role, taking much pride in their work. We aim to continue innovating in the future, giving businesses the upper hand on their energy decisions.

Job Description

We are seeking for a candidate who is passionate about making a difference in energy industry using data analytics. Energy Data Analyst will act as a bridge between our data science team and the energy market. He/she will use data analysis techniques to find answers to research questions raised by data science team, will evaluate the challenges and opportunities in the market, backing the findings with solid statistics, and will evaluate and analyze our products' performance, providing insightful feedback for improvements, just to count a few of the responsibilities. 

The ideal candidate is experienced and comfortable with analyzing big data and crunching numbers, is familiar with the electricity wholesale markets in the US, and has programming background, preferably in Python. We are seeking independent and critical thinkers, who are good team players.

Qualifications

  • Strong background in data analytics. Must be familiar with basic statistical techniques and metrics, such as implementing and evaluating regression analysis, hypothesis testing, auto-correlation, probability distributions, graphical representations, as well as confusion matrices to evaluate accuracy, precision and error, etc. (Machine Learning background is a plus).
  • Strong understanding of energy markets in US (Previous work experience in the energy domain, or extensive coursework and projects in the area)
  • Familiarity with using Python for data analysis (or equivalent language).
  • A strong sense of ownership
  • A team player
  • Strong verbal and written communication skills

Additional Information

COMPENSATION

Very competitive salary, because you deserve it. 

Equity in the company, to keep you motivated.

401(k) plan with matching, because we care about your future!


PERKS:

Unlimited vacation, we work hard and take time when we need it.

Medical, dental and vision coverage.

Fully stocked fridge, coffee, espresso and tons of snacks to keep us going.

Fantastic modern office space in Pittsburgh’s Strip District with free parking.

Great office environment with exceptionally talented coworkers.

kWantera’s staff is highly motivated to shake up the status quo of the modern electric and natural gas industries within the United States. Our technology platform, machine learning, and predictive analytics are cutting-edge entrants into the emerging world of Big Data. We seek people who will be similarly passionate about changing the world.

Skills Required

  • Strong background in data analytics, including regression, hypothesis testing, auto-correlation, probability distributions, and evaluation metrics (confusion matrices).
  • Familiarity with using Python for data analysis (or equivalent language).
  • Experience analyzing big data and numeric datasets.
  • Strong understanding of US energy markets (wholesale electricity markets) through work experience or extensive coursework/projects.
  • Strong verbal and written communication skills.
  • A strong sense of ownership and ability to work as a team player.
  • Machine learning background.
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The Company
Pittsburgh, PA
63 Employees

What We Do

kWantera changes the way energy is bought, sold, and consumed.

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