Principal Data Scientist
To see similar active jobs please follow this link: Remote Development jobs
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.
About the job
Principal Data Scientist
To see similar active jobs please follow this link: Remote Development jobs
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.