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As a data scientist at GridCure, you will be developing algorithms that will revolutionize data analytics in the utility industry. GridCure is working with utility companies to develop better analytical tools for preventative maintenance, load prediction, and outage prediction. We are a small but growing team, so you will have the opportunity to make real creative contributions to GridCure’s analytical product.

Typical duties:

• Data cleaning: GridCure’s ability to make use of utility data in a wide variety of formats is one its strengths. You will be involved in parsing, cleaning, and standardizing datasets.
• Data exploration: You’ll develop an understanding of new datasets as they come in and interact with clients to better understand the data.
• Data modeling: You’ll be involved in building and benchmarking new models and improving old models. You’ll document differences between different versions of models.
• Analysis tooling: You’ll develop tools to help clients better understand their data.
• Model deployment: You’ll be involved in scaling models for production.

Requirements:

• A passion for understanding data.
• Experience programming in python.
• Experience cleaning realistic datasets.
• Experience building predictive models based on a variety of data.
• Deep knowledge of at least one area of predictive modeling.
• Energy industry experience or interest.

Please include a resume and a sample of your work.

Optional Predictive Modeling Challenge:

Files for Electric Car Practice Problem

As a data engineer at GridCure, your general responsibilities will include bolting together the core components of our platform that allow us to interact with utility company data stores, helping build systems to better catalogue and analyze smart grid data, and creating features to automate the process of launching analytical models as new clients come on board.
More specific to this role, you’ll be in charge of building and managing ETL pipelines for batch and streaming data that comes to us from utilities all around the world. Familiarity with significant differences in velocity of data entering a given pipeline, processing error handling/logging (data is never consistently clean), and containerization/autoscaling of services are key.

About Your Background:

We use cloud infrastructure, and we’re looking for familiarity with the standard Amazon Web Services and Google Cloud offerings. Most of our clients use more traditional database systems to store their smart grid data, and familiarity with working with some older-school system integrations is helpful. We want to hear your enthusiasm and experience dealing with changing data formats and how you’ve handled that in the past, your stories about ‘that one crazy file format we had to parse’, and how you built systems that scaled up to handle large data flows overall.
We also value experience in the utility space (bonus points if you can tell us the difference between AMI and AMR), and experience deploying production ETL pipelines to enterprise-scale customers that you’ve babysat for a little while. We’re mostly a python shop, so experience with python required.

About the Role:

As a back-end developer at GridCure, your general responsibilities will include bolting together the core components of our platform that allow us to interact with utility company data stores, helping build systems to better catalogue and analyze smart grid data, and creating features to automate the process of launching analytical models as new clients come on board.
More specific to this role, you’ll be spending a lot of time working with to make sure the connections and communications between our backend systems and front-end UI components and modules are working properly. You’ll spend a lot of time in Django, be one of our key people making sure we’ve got proper segregation between user data where it’s required client to client, and fundamentally helping us decrease our time to deploy to our customers.

About Your Background:

We use cloud infrastructure, and we’re looking for familiarity with the standard Amazon Web Services and Google Cloud offerings. Most of our clients use more traditional database systems to store their smart grid data, and familiarity with working with some older-school system integrations is helpful. We’re a python shop, and a background in Django background is key. Knowledge about Google’s hosted Kubernetes clusters (and perhaps most importantly, when *not* to use containers) is good knowledge to have as well.
We also value experience in the utility space (bonus points if you can tell us the difference between AMI and AMR), and experience deploying applications with very strict user and data security will be valuable.

About the Role:

As a back-end developer at GridCure, your general responsibilities will include bolting together the core components of our platform that allow us to interact with utility company data stores, helping build systems to better catalogue and analyze smart grid data, and creating features to automate the process of launching analytical models as new clients come on board.
More specific to this role, you’ll be spending a lot of time working with to make sure the connections and communications between our backend systems and front-end UI components and modules are working properly. You’ll spend a lot of time in Django, be one of our key people making sure we’ve got proper segregation between user data where it’s required client to client, and fundamentally helping us decrease our time to deploy to our customers.

About Your Background:

We use cloud infrastructure, and we’re looking for familiarity with the standard Amazon Web Services and Google Cloud offerings. Most of our clients use more traditional database systems to store their smart grid data, and familiarity with working with some older-school system integrations is helpful. We’re a python shop, and a background in Django background is key. Knowledge about Google’s hosted Kubernetes clusters (and perhaps most importantly, when *not* to use containers) is good knowledge to have as well.
We also value experience in the utility space (bonus points if you can tell us the difference between AMI and AMR), and experience deploying applications with very strict user and data security will be valuable.