What We Are Building
We’re a small team with big dreams. Harvard born & Y Combinator backed, we’re a startup taking on big challenges. Our first focus is reshaping lab testing for large industries like oil & gas. We might be from different places, and bring different talents to the table, but we’re all here for the same reason. To transform large industry verticals and make a dent in the world, with the smartest people we know. Join us – you might like it here.
As a Data Scientist, you will:
- Combine rigorous statistical analysis with first-principles insights from physics and chemistry to improve the accuracy and efficiency of customers’ instrumentation and measurement practices
- Build data infrastructure and automated analytics tools
- Build visualization tools to explain insights to the relevant stakeholders (field technicians, measurement managers, traders and executives)
- Growth mindset, passion for learning new things, restlessness
- First-principles thinking – you have the strong desire to understand any topic at a deeper level than most, and are unsatisfied with decisions based on convention or unjustified assumptions
- Ability to formulate and test hypotheses quickly and efficiently
- Experience in setting up the data infrastructure for projects
- Understanding and experience with basic (e.g. random forest, SVMs) and advanced (e.g. deep learning, stochastic processes) machine learning methods
- Comfortable building utility code and handling miscellaneous support tasks
- Strong proficiency with Python and common data science packages (NumPy, Pandas, SciPy)
- Experience with relational databases and comfortable with SQL query syntax.
- Comfortable working with disparate data sources (i.e SQL, CSV, APIs) and familiar with data source normalization pipelines
- Advanced degree (MSc or PhD) in computer science, engineering or another mathematically related field (e.g. Physics, Math, Statistics, etc.), or equivalent research relevant experience outside of academia
- Basic understanding of physics, chemistry (1st or 2nd year level)
- Any exposure to large industrial processes, chemical/biochemical analysis and/or logistics
- Experience with TensorFlow, Keras, PyTorch, Spark, SciKit Learn, or other libraries related to machine learning, signal processing and data visualization.
- Comfortable with real-time data pipelines or stream-processing platforms such as Kafka
- Comfortable with Unix like operating systems (Linux, MacOS X) and command line interfaces
Who We Are
We are a group of intellectually curious people who are passionate about bringing innovation to large industries like oil & gas. If you would like to join a fast-paced, rapidly changing and exciting start-up and think this description sounds like you, please send your resume and relevant links (Github, LinkedIn) to email@example.com, and complete the form below.