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New Relic · 1 day ago

Lead Data Scientist

Portland, OR

Full-time

Hybrid

Senior Level, Lead/Staff

$163K/yr - $204K/yr

7+ years exp

New Relic is a global team of innovators and pioneers dedicated to shaping the future of observability. As a Lead Data Scientist, you will drive the development of advanced data products and machine learning solutions, working across product, engineering, and strategy to derive insights from telemetry data.

AnalyticsApplication Performance ManagementCloud ComputingIT InfrastructureMobileSaaSSoftware

Comp. & Benefits

No H1B

Responsibilities

Lead the design, development, and deployment of advanced ML models and predictive algorithms to solve critical business problems, such as churn prediction, user segmentation, and product usage forecasting

Serve as a technical subject matter expert, guiding the team on best practices in statistical analysis, experimentation design, and code quality

Partner with PMs and Engineers to translate ambiguous business questions into rigorous data science projects with actionable outcomes

Drive the adoption of MLOps best practices, ensuring models are scalable, reproducible, and monitored effectively in production

Perform deep-dive analyses on user behavior and product performance to identify opportunities for optimization and growth

Mentor and coach other data scientists and analysts, fostering a culture of continuous technical learning and innovation

Communicate complex technical findings to non-technical stakeholders through compelling data storytelling and visualization

Qualification

Machine LearningPythonSQLMLOpsData VisualizationGenAI ModelsStatistical AnalysisSoftware Engineering PracticesCommunication SkillsMentoring

Required

7+ years of experience in DS, Statistics, or a related field, with a proven track record of delivering high-impact machine learning solutions

Expert-level proficiency in Python for data manipulation, statistical analysis, and model development (pandas, scikit-learn, numpy, etc.)

Advanced knowledge of SQL for complex data querying and performance optimization

Strong hands-on experience with a breadth of modeling techniques, including: Supervised learning (Regression, Random Forests, Gradient Boosting like XGBoost/LightGBM), Unsupervised learning (Clustering, Dimensionality Reduction), Time series forecasting (ARIMA, Prophet)

Experience with dbt for data transformation and maintaining clean, reliable data pipelines

Demonstrated ability to deploy models into production environments and familiarity with MLOps concepts

Familiarity with software engineering practices (CI/CD, version control with Git, Jira)

Strong communication skills, with the ability to influence stakeholders and explain technical concepts to business audiences

Expertise in developing or integrating GenAI models or AI agents into product and analytical workflows