ML Ops Data Scientist

Company Overview

BlueConduit is an infrastructure analytics SaaS company and social enterprise founded in 2019. We have focused on serving water utilities and pioneered the predictive modeling approach to lead service line and water main risk identification and replacement. Prior to starting the company, our founding team members were first to model the distribution of lead pipes in Flint, Michigan. We now help cities throughout North America model risk and meet compliance across multiple water distribution assets, including service lines, water mains, and more. We are passionate about using data science for social good and improving equity. Through our software platform, utilities, municipalities, government agencies, and consultants standardize, predict, report, and communicate key information about water infrastructure. BlueConduit operates as a remote-first organization.

Our software enables utilities to focus their resources where risk is highest, thereby improving the quality and reliability of drinking water, especially for vulnerable communities, and saving millions of dollars. BlueConduit has worked with more than 400 cities and inventoried over 5 million service lines, saving our customers over $300M and years of added work.

Job Description

BlueConduit is hiring a Machine Learning Operations / Data Scientist to put cutting-edge data science work into production code, embedded in our software that serves our customers. That data science work involves building and deploying machine learning pipelines to predict risk in water distribution infrastructure.

Responsibilities

- Build in more automated processes with latest AI tools to improve machine learning models performance and efficiency of cloud-based data pipelines

- Work closely with Software Engineering and Product to seamlessly integrate data science code into the production code of our software.

- Actively engage in R&D to continually scale the impact of BlueConduit's predictive methods

- Use machine learning pipelines and other internal tools to provide risk predictions for water distribution assets

- Support non-technical clients with data analysis and clear communication of model results on tight timelines

This role will report to the VP of Data Science.

We are a small, remote, and growing team, so this is an excellent opportunity to grow into and shape your role at our company. The role provides opportunities for mentorship and for taking on leadership responsibilities.

Qualifications:

- Curiosity to learn and commitment to the human side of data science

- Passion for data science for social good and environmental justice

- Independent problem-solving

- Excellent verbal and written communication skills

- Undergraduate degree in quantitative field (e.g., CS, math, stats, physics, etc.)

- Substantial experience with Python, especially pandas, Scikit-learn, PySpark, and numpy

- Extensive experience (~5+ years) with machine learning and statistical models, including validation and evaluation of model performance

- Machine Learning Operations (MLOps) experience

- Experience building production code based on solid data science work

- Experience building and improving machine learning models and data pipelines

- Experience using latest AI tools for implementing ML/ DS work in production software

- Experience deploying, monitoring, and maintaining machine learning models in production environments

- Experience building production-level ML pipelines using PySpark (or Spark in Scala)

- Experience with issues related to modeling (e.g., selection biases, causal inference)

- Experience working with messy data, iterating with clients on a shared dataset

- Ability to build and maintain strong documentation habits

- Proficiency with Git workflow

- Experience building models and pipelines in Databricks

Nice-to-have Qualifications:

- Graduate degree in a quantitative field

- Experience using distributed computing

- Experience with Agile product development (e.g., sprints, standups, scrums)

- Experience working with geospatial models, modern GIS systems, and geospatial data science tools (geopandas, shapely, rasterio, geodal, etc)

- Familiarity with infrastructure, water quality, or government data

Location: Remote

Compensation:

- Salary range ($125-145K), commensurate with experience

- Stock options

- Health benefits (100% coverage of medical premiums for a base plan or a portion of a premium plan; Vision and Dental also available)

- Simple IRA benefit (3% company contribution matching)