LawIQ | ENERGY INFRASTRUCTURE DATA SCIENTIST - Technical.ly

ENERGY INFRASTRUCTURE DATA SCIENTIST

LawIQ | Washington, D.C. | Data Science

Job Description
Company Culture
Technical.ly Coverage

OVERVIEW

Join a dynamic, growing Software-as-a-Service (SaaS) company delivering business intelligence analytics and advisory services to blue chip customers in the energy and financial industries to explain and predict regulatory, legal, and market events by combining proprietary AI technology with industry expertise.

The LawIQ team seeks smart, driven, and curious teammates interested in pursuing rapid professional growth at the intersections of data-driven technologies, energy infrastructure, law, and regulatory policy to join our data science and software engineering team.

This position offers the opportunity to drive development of our machine learning (ML) based predictive technologies used by leading energy and financial companies to forecast the feasibility and timing of major projects, such as natural gas pipelines, that are enabling America’s energy independence.

Your technical knowledge of ML algorithms and statistical modeling techniques, combined with your desire to work with customers to inform their business critical decisions will make a significant contribution to LawIQ’s growth and enable you to autonomously operate and expand the analytical tech stack and build the data science team.

ABOUT THE POSITION

The Energy Infrastructure Data Scientist (EIDS) with the data science and software engineering team to expand the predictive technologies embedded in LawIQ’s energy analytics SaaS platform. By interacting with large disparate textual data sets and API interfaces, the EIDS will identify, build, and maintain new feature sets and value driving product extensions. The dynamic and unique customer needs we address allow for creativity and experimentation with new techniques.

Responsibilities will include:

  • Analyzing disparate data sets of textual regulatory filings and applying statistical modeling techniques to derive patterns and insights to generate probabilistic decision support models.
  • Applying ML algorithms such as random forest and gradient boosting to ensemble models to continuously improve their predictive capabilities of energy regulatory processes.
  • Collaborating with the research and commercial teams and interacting with customers to understand their use cases and need for data driven decision support and address via software product development and delivery of advisory services.
  • Utilizing multiple data visualization tools and techniques to wrangle data sets ingested by our proprietary data acquisition systems and conducting analyses to transform the data into clear compelling visuals.

ABOUT YOU

Driven, dedicated, data obsessed and design oriented.  You are able to quickly gain the trust of team members and have a demonstrated pattern of success and initiative, a desire to learn, and the ability to thrive in a fast paced entrepreneurial environment.

YOU HAVE

  • Education – Bachelor’s of Science degree in a related field. MS preferred.
  • Functional knowledge :

– experience applying multiple statistical modeling techniques including linear and nonlinear regression, and regularization methods

– exposure to and understanding of Bayesian modeling

– proficiency with ML algorithms and ensemble modeling techniques including random forest and gradient boosting

– understanding of key ML concepts such as hyperparameter optimization and model assessment and evaluation

– mastery of R and Python

– working knowledge of visualization libraries such as ggplot2 and matplotlib

– understanding of relational databases and NoSQL databases

– experience interacting with APIs

– exposure to neural network platforms such as Tensorflow or PyTorch

  • An interest in the energy industry and associated technology, policy, legal, and regulatory domains
  • Exposure to and desire to work in entrepreneurial environments

 YOU MAY HAVE OR SEEK

  • Experience engaging customers in consultative role
  • Experience working with agile development processes, tools, and teams
  • Experience leading team(s)

Work Environment:  LawIQ has offices in Washington, DC, Baltimore, MD, and a satellite in Denver, CO.  We offer a collaborative and flexible work environment that includes opportunities for professional development and to work remotely.

 Equal Opportunity:  LawIQ is committed to the recruitment, hiring, and promotion of qualified individuals and does not discriminate based on race, color, national origin, gender, affectional or sexual orientation, age, religion, disability, or veteran status.

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How would you describe what makes LawIQ unique:

We’re a bit of a hybrid company in that we bring the best of Silicon Valley and Washington D.C. together. We marry that software, data and tech mentality with a deep expertise usually found in close proximity to government.  It is an interesting intersection - a unique for-profit energy technology business in the District contributing to better relations between regulators and infrastructure developers.

Replacing opinions and positions with data and evidence leads to a more transparent process between all stakeholders.

What is the mission behind the work you do at LawIQ?

Energy is the world’s largest industry and it generates a lot of conflict. Anything that can better balance access to energy around the world, can also is some ways promote peace. We want to help the energy industry build capacity, and bolster the United States’ ability to be independent in that regard, which leads to more options in how we engage geopolitically.

A few of us, including our founders, served in the military. The work we’re now doing crosses over into what a lot of people come to D.C. to do: to serve the greater good.

What is the culture like at LawIQ?

We have a very collaborative culture. We’re still small enough that everyone has a vote in big decisions, such as how we move forward and who we hire. That may change as we grow, but we’ll work hard to stay flat.

We’re incredibly customer-centric — there’s no solution proposed without customer input, which requires developing and maintaining great relationships with our diverse customer base. Our decisions cross through a lot of teams, so everyone is required to understand the entire matrix of what we do. We take pride in our depth of expertise and love seeing it benefit to our customers.

We are also a bit contrarian. We’re not afraid to have non-mainstream viewpoints. Even if it’s not what the customer wants to hear, we’ll put out and defend ideas that we believe will make a big impact for our them.

In terms of work style, employees are trusted with a tremendous amount of responsibility and ownership. We do the opposite of micromanage. Additionally, folks are offered a lot of flexibility between their work and home lives, and can work from home when needed.

What do you look for in job candidates?

We are looking for people who are curious self-starters, internally-driven, confident and who think like an owner. People who don’t want to just stay in their lane.

We want people with a deep functional expertise, but also a general curiosity about working across other functions of the company. For instance, a software engineer who doesn’t mind getting in front of a customer to present the tech they’ve built. All of our roles support customers in one way or another, so it’s important that candidates are enthusiastic about that.

Ultimately, an ideal candidate wants to understand all aspects of our business, the industry and our larger purpose. What our industry is doing is important. We want you to care about the global implications.

What kinds of tech skills do you expect candidates to have?

Being in this field, a lot of our tools and technology are made around data science, from text extraction to data modeling to running machine learning models. The tools, software techniques and user interfaces we utilize are all cutting edge.

Skills that we hope candidates will have are:

  • Software Engineers: experience with Python, scalable APIs using AWS, cloud computing
  • Data Science: experience with statistical modeling and machine learning technology for predictive models and with data visualization languages and tools like R and associated libraries.

We are also committed to giving our employees opportunities to create their own custom learning paths, so we facilitate educational opportunities as much as possible via tools like Linkedin Learning, and with company offsites. Employees are also welcome to try out new tech and introduce it to the team.

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