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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in building and maintaining end-to-end machine learning systems while translating complex business problems into actionable insights. Proficient in leveraging data to optimize user experiences and inform strategic decisions across various stakeholders.
Highest-signal resume keywords
Machine Learning EngineeringData ScienceGoogle Cloud PlatformStatistical ModelsSupervised and Unsupervised Learning
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Machine LearningPredictive ModelingData AnalysisData VisualizationStatistical AnalysisCausal ModelingSession-Level PredictionsUser SegmentationContent Viewership PredictionDiagnostic Analysis
Soft Skills
Concise CommunicationDetail OrientationPersuasive CommunicationCollaborationInnovation
Tools & Technologies
Google Cloud PlatformBigQueryML EngineAPIsAtlassian JIRAAtlassian Confluence
Certifications & Qualifications
MS in StatisticsPh.D in Data SciencePh.D in Computer Science
Industry Keywords
MLOpsData Science SolutionsUser Behavior PredictionSubscription JourneyCohort-Based Targeting
Tech Stack
Tools & technologiesBigQueryCloudGoogle Cloud Platform
About the role
Key responsibilities & impact- Build ML products that shape business strategy, optimize content, inform marketing investment decisions, and enhance user experience
- Leverage video and ads consumption, clickstream activity, subscription history, and 2nd/3rd party data to build user- and session-level causal and predictive models
- Translate complex business problems into actionable quantitative solutions
- Implement, automate, and maintain reliable, performant end-to-end ML systems using software engineering and MLOps best practices
- Deliver clear, impactful insights to stakeholders
- Collaborate with Product stakeholders to operationalize data science solutions
- Promote best practices across the data science and product analytics team
- Build global models predicting user behavior throughout the subscription journey
- Identify and measure high-value user actions and drivers of habit formation
- Develop session-level predictions to uncover user intent
- Predict content viewership and identify content traits that resonate with subscribers
- Create user segmentations for cohort-based targeting and near-personalized experiences
- Perform diagnostic analyses, including evaluation of failed searches, to identify product improvement opportunities
Requirements
What you’ll need- 2+ years experience in Data Science and ML Engineering
- MS or Ph.D in Statistics/Data Science/Computer Science or related disciplines with specialization in machine learning techniques
- Experience with supervised and unsupervised learning methodologies
- Full stack experience in data collection, aggregation, analysis, visualization, productionalization, and monitoring of data science products
- Familiarity with statistical and ML models and methods
- Ability to innovate without over-engineering
- Concise and persuasive communication with a wide variety of stakeholders
- Strong detail orientation and focus on data accuracy
- Experience using Google Cloud Platform, including BigQuery, ML Engine, and APIs
- Experience integrating AI solutions into existing business processes
- Experience using Atlassian project management tools such as JIRA and Confluence
Benefits
Comp & perks- Medical insurance
- Dental insurance
- Vision insurance
- 401(k) plan
- Life insurance coverage
- Disability benefits
- Tuition assistance program
- PTO / generous paid time off
- Bonus eligibility
- Attractive compensation and comprehensive benefits packages
- Opportunities for on-site and virtual engagement events
- Opportunities to build meaningful connections and a vibrant community
