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Principal Data Scientist (Remote, US)

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Location
United States
Base Salary
223k-268k USD
Grafana Labs

Job Description

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 Grafana Labs: There are more than 20M users of Grafana, the open source visualization tool, around the globe, monitoring everything from beehives to climate change in the Alps. The instantly recognizable dashboards have been spotted everywhere from a NASA launch and Minecraft HQ to Wimbledon and the Tour de France. Grafana Labs also helps more than 3,000 companies -- including Bloomberg, JPMorgan Chase, and eBay -- manage their observability strategies with the Grafana LGTM Stack, which can be run fully managed with Grafana Cloud or self-managed with the Grafana Enterprise Stack, both featuring scalable metrics (Grafana Mimir), logs (Grafana Loki), and traces (Grafana Tempo). Benefits: For more information about the perks and benefits of working at Grafana, please check out our careers page. Equal Opportunity Employer: At Grafana Labs we’re building a company where a diverse mix of talented people want to come, stay, and do their best work. We know that our company runs on the hard work and the dedication of our passionate and creative employees. If you're excited about this role but your experience doesn’t align perfectly with every qualification in the job description, we encourage you to apply anyways. We will recruit, train, compensate and promote regardless of race, religion, color, national origin, gender, disability, age, veteran status, and all the other fascinating characteristics that make us different and unique. We believe that equality and diversity builds a strong organization and we’re working hard to make sure that’s the foundation of our organization as we grow. For information about how your personal data is used once you’ve applied to a job, check out our privacy policy.

Advice from our career coach

As the founding member of the predictive analytics practice within a remote Principal Data Scientist role at Grafana Labs, it is essential for successful applicants to possess extensive experience in deploying ML models on time series data and coordinating between teams to meet business-driven timelines. To standout as an applicant, here are some specific tips and insights:

  • Highlight your experience in building production-ready ML models for time series applications.
  • Showcase your ability to establish shared standards and best practices for data science.
  • Emphasize your quantitative background with an MS/PhD in a related field.
  • Demonstrate proficiency in Python, SQL, and cloud data warehouses like BigQuery or Redshift.
  • Illustrate your motivation as a self-starter who can tackle complex problems and make a significant impact.
  • Focus on your communication skills to effectively explain technical concepts to non-technical audiences and collaborate cross-functionally.
  • If possible, highlight any experience with Bayesian statistics, observability, or Grafana visualization.

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