Staff Data Scientist (Remote, US)

Details

This is a remote position, and we’re considering candidates in the United States time zones.
There are more than 950,000 active installations of Grafana around the globe, monitoring everything from beehives to climate change in the Alps. The instantly recognizable dashboards have been spotted everywhere from a SpaceX launch and Minecraft HQ to Wimbledon and the Tour de France. Grafana Labs also helps companies including Bloomberg, JPMorgan Chase, and eBay manage their observability strategies with full-stack offerings that can be run fully managed with Grafana Cloud, or self-managed with Grafana Enterprise Stack. The Grafana stack has grown to include two other open-source projects, Grafana Loki (for logs) and Grafana Tempo (for traces).

About the Role

We are looking for a Staff 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 metric 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.

Responsibilities

• 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

Requirements

• Extensive experience building production-ready ML models for time series applications
• 5 - 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

Location

United States (Remote)

Compensation

In United States, the base compensation range for this role is USD 196,267 - USD 245,784. Actual compensation may vary based on level, experience, and skillset as assessed in the interview process.