Principal Data Scientist

This is a remote position and we’re considering candidates in the Canadian 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 Canada the base compensation range for this role is CAD 213693 - CAD 256431. 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.