This is a remote position, and we’re considering candidates in the United States time zones. 

About the Role

We are looking for a Principal Data Scientist to be the founding member of our predictive analytics practice within our Data & Analytics team, with a focus on building capabilities around operationalizing ML models to drive core financial metrics and customer consumption forecasts. In particular, this function will be a key driver in corporate planning and will be heavily relied upon by teams across Finance, Revenue Operations, and our executive team.

Success in this role will require a combination of significant experience in deploying ML models on time series data, coordinating between multiple teams to meet business-driven timelines, and an ability to establish standards and best practices for data science across Grafana Labs.

Examples of projects you’ll work on

• Refine our existing time series forecasts to allow the prediction of per-customer consumption, with an emphasis on ensuring model explainability and a clear representation of model uncertainty
• Partner with Data Engineering to ensure the model infrastructure is in place to serve, monitor, test, and retrain any models put into production
• Identify and build solutions to leverage these forecast models for operational use cases (e.g., customer consumption anomaly detection, alerting, etc.)
• Partner closely with RevOps to both understand and predict customer consumption as a part of our sales planning and territory management
• Collaborate across Product, R&D, and Data Engineering to identify and ingest new sources of data to improve model performance

What you bring

• Extensive experience building production-ready ML models for time series applications
• Experience establishing shared standards, best practices, and expectations of data science
• MS/PhD in a quantitative discipline (Math, Statistics, Operations Research, Economics, Engineering, or CS)
• 7+ years of experience with Python and familiarity with SQL
• Hands-on experience with cloud data warehouses (e.g., BigQuery, Snowflake, Redshift, etc.)
• Highly motivated self-starter that is keen to make an impact and is unafraid of tackling large, complicated problems
• Excellent communication skills, able to explain technical topics to non-technical audiences, and maintain many of the essential cross-team and cross-functional relationships necessary for the team’s success

A plus if you have

• Experience in Bayesian statistics and modeling
• Knowledge about observability
• Previous experience with Grafana visualization, or a desire to invest the time to learn

In United States, the base compensation range for this role is USD 223,254 -  USD 267,905 Actual compensation may vary based on level, experience, and skillset as assessed in the interview process. Benefits include equity, bonus (if applicable) and other benefits listed here.

*Compensation ranges are country specific. If you are applying for this role from a different location than listed above, your recruiter will discuss your specific market’s defined pay range & benefits at the beginning of the process.