Data Scientist

Apply to the "Data Scientist" role at https://welligence.com - scroll down to the data scientist posting, expand the post, and click the apply button. Please include your Github and LinkedIn accounts in your cover page or resume.

At Welligence we’re on a mission to transform the energy industry by building the world’s leading international data platform. Clients across five continents use our data intelligence platform to make business critical decisions, perform macro analysis, do granular deep dives on specific opportunities, and ultimately increase profits and minimize carbon emissions. We’re backed by leading energy investors Quantum Energy Partners, and have offices in Austin, Houston, London, and Edinburgh.

As a Data Scientist on our Austin-based team you will join an industry-leading group under Head of Data Science Akash Sadashivapeth and working closely with Harvard professor and Co-founder Seth Neel. Our team is comprised of diverse backgrounds across statistics, computer science, and electrical and petroleum engineering.

• Forecasting and tracking of carbon emissions into the atmosphere

• Customer analytics using Google Analytics APIs

• Data visualizations to help clients (energy companies, banks, investors) make informed decisions

• Data-heavy consulting or projects for subscription clients

• You’ll work up to contributing to our time series forecasting and machine learning in R using our proprietary library

You will also gain valuable insight into the energy industry by working with our in-house team of over a dozen recognized global experts and play a vital role in applying data science to the energy transition.

• The desire and passion to learn new technical skills and concepts quickly and to push the boundaries of current systems

• Top-notch communication with stakeholders, investors, clients, and your teammates

• The confidence to ask for help when needed

• Ability to prioritize work and manage your time

• Experience manipulating and cleaning large datasets in R, pulling data in SQL, and using version control with Git

• Experience with Unix-like operating systems (Linux, MacOS X) and command line interface

• Ability to work with disparate data sources (i.e SQL, CSV, APIs)

• 1-3 years of experience in R (Rshiny, ggplot2, tidyverse, ggplot2, plotly)

• Basic familiarity with concepts in machine learning (time series, decision trees, linear regression, clustering)

• Engineering best practices: git, agile/kanban methodologies, code documentation

• Experience designing relational databases/ERDs (nice to have)

• Experience running ML algorithms in AWS or similar platforms (nice to have)

• Competitive compensation, stock options (included in this position), and health benefits

• Equity options in a well-run and financially stable tech company that has potential for massive upside

• Flexible working arrangements (1 day of your choice WFH)

• Chance to make a real impact in the trillion $ global energy industry

• Emphasis on learning new concepts and growing your data science career (professional development budget to take courses if desired)

• Flat culture emphasizing collaboration, merit, and communication

• Opportunity for rapid advancement

• Your teammates will respect your time and fully expect you’ll lead a balanced life, while working hard when you’re at work.

This role is in-person, full-time, based in Austin, Texas.