Data Scientist with Google Cloud Platform

Key requirements

• Proficient in SQL/Python
• Must have knowledge/experience on A/B tests, statistical analysis, machine learning
• Preferred Healthcare experience
• Preferred MS with 2-3 years of experience

Overview

• Project / Initiative: Data science support for campaign development and ML-driven member engagement (e.g., kidney disease campaigns)
• Business Objective:
• Improve member engagement and campaign effectiveness using data-driven insights and machine learning
• Translate analytical outputs into measurable business impact (ROI, KPIs)
• Current State / Problem:
• Existing ML models and campaigns need stronger ownership, productionization, and evaluation
• Gaps in data quality validation and production readiness
• Need for better linkage between data analysis and business impact
• Desired Outcome:
• Hire a senior-level data scientist who can independently build, deploy, and evaluate models while tying outputs to business outcomes
• Improve campaign ideation, execution, and measurement with a stronger experimentation framework

Role Summary

• Role Title: P2 Data Scientist
• Reason for Opening:
• Support ownership and scaling of existing ML models and campaign initiatives
• Expand new campaign concepts (i.e. kidney disease) with stronger analytical rigor
• How this role fits into the broader project:
• Acts as a bridge between data engineering, analytics, and business stakeholders
• Drives campaign ideation, modeling, production deployment, and performance evaluation
• Team Structure / Reporting Line:
• Works alongside data engineers (pipeline & deployment support)
• Partners with business stakeholders and P3-level team members for problem scoping
• Expected to operate with moderate independence

Key Responsibilities

• Design, build, and deploy machine learning models at production scale
• Take ownership of existing ML models and improve performance and reliability
• Develop and launch data-driven marketing campaigns
• Partner with data engineers to productionize pipelines (DAGs, workflows)
• Conduct campaign sizing and impact analysis (ROI, KPI development, assumptions)
• Evaluate campaign effectiveness post-launch using proper experimentation methods
• Translate ambiguous business problems into analytical approaches and solutions
• Ensure data quality, validation, and production readiness of outputs
• Identify new campaign opportunities and propose innovative data-driven ideas
• Analyze model outputs and continuously optimize performance

Must Haves

• Strong SQL and Python (independent development required)
• Experience building and deploying ML models in production environments
• Experience with data pipelines and workflow orchestration (e.g., DAGs)
• Working knowledge of cloud data platforms (Google Cloud Platform preferred)
• Data validation, quality assurance, and production readiness practices
• Experience with experimentation and A/B testing
• Strong analytical thinking for sizing problems and estimating business impact
• Ability to define and align on KPIs and success metrics
• Experience evaluating model effectiveness
• Strong business acumen (ability to connect data insights to business outcomes)
• Ability to work with ambiguous, open-ended problems
• Attention to detail (sanity checks, data validation)
• Strong collaboration with cross-functional teams (engineering + business)
• Proactive ideation and problem-solving mindset

Preferred Skills (Nice-to-Haves)

• Healthcare domain experience (especially member engagement/use cases)
• Prior campaign management or marketing analytics experience
• Familiarity with Claude or AI-assisted workflows
• Experience with campaign configuration platforms

Tech Stack

• SQL
• Python
• Google Cloud Platform (Google Cloud Platform)
• BigQuery
• Vertex AI
• DAG-based orchestration tools
• Visual Studio
• Claude (AI tooling, optional but desirable)