Remote Data Scientist Graduate Jobs in California

Data Scientist III

Duration: 12-Month Contract (Strong Potential for Extension)
Schedule: 40 Hours/Week (Monday-Friday)
Pay Rate: $85 per hour

Location: Remote (Pacific time hours)

Our client, a global technology leader seeking a Data Scientist for FY27. This individual will partner with marketing stakeholders to define and measure key business metrics and identify and execute on opportunities to improve performance and positively impact business results.

Responsibilities

• Performs business analysis using various techniques, e.g., statistical analysis, explanatory and predictive modelling, and data mining.
• Determines best practices and develops actionable insights and recommendations for current business operations.
• Works directly with internal or external clients to identify analytical requirements.
• Produces ad hoc data analyses and reports.
• Assists in implementing or developing systems to capture business operation information.
• May occasionally guide less experienced business data analysts.

Required Qualifications

• 7-10 years of overall experience preferred
• Experience in CRM, lifecycle marketing, or marketing analytics is highly preferred and considered important for success
• SQL Proficiency: Writing complex queries to extract, join, and transform data from relational databases.

• Data Visualization Tools: Expertise in tools like Qlik Sense for building dashboards and reports.
• ETL Knowledge: Familiarity with data pipelines and tools (e.g., Superglue, Alteryx, Informatica, dbt, Airflow).
• Statistical Analysis: Understanding of statistical methods, A/B testing, regression analysis, and forecasting.
• Scripting Languages: Python or R for advanced data analysis and automation (nice-to-have).
• Lifecycle Marketing Knowledge
• CRM Strategy & Lifecycle Marketing: Understanding of customer lifecycle stages, retention strategies, customer journeys, and lifecycle campaign optimization.
• CRM Performance Metrics: Knowledge of KPIs such as open rate, click-through rate (CTR), click-to-open rate (CTOR), conversion rate, unsubscribe rate, churn, retention, customer lifetime value (LTV), and engagement metrics.
• Segmentation & Personalization: Experience with audience segmentation, customer targeting, personalization strategies, and dynamic content to improve campaign performance.
• Campaign Measurement & Optimization: Ability to measure, analyze, and optimize CRM campaigns across email, push notifications, SMS, in-app messaging, and other owned channels.
• Customer Journey Analytics: Understanding of customer behavior, funnel analysis, cohort analysis, and journey performance to identify opportunities for improving engagement and retention.
• Experimentation & Testing: Knowledge of A/B and multivariate testing methodologies to evaluate messaging, timing, audience segmentation, and campaign effectiveness.
• CRM Platforms & Data Integration: Familiarity with CRM platforms (e.g., Braze) and the integration of customer data for reporting and analytics.
• Business Impact Analysis: Ability to connect CRM initiatives to business outcomes, including revenue, customer retention, engagement, and loyalty metrics.
• Data & AI Competencies
• Dashboard Creation: Designing user-friendly, automated dashboards for marketing stakeholders.
• Data Storytelling: Translating raw data into clear insights and actionable recommendations.
• Data Governance: Ensuring data accuracy, consistency, and compliance with established standards.
• KPI Frameworks: Defining and maintaining standardized marketing metrics and reporting structures.
• AI Agent Workflow Automation: Understanding of AI agents and automated workflows to streamline reporting, insights generation, and business process execution.
• Prompt Engineering: Ability to design effective prompts and instructions for AI-assisted data analysis and reporting.
• Process Automation: Experience identifying repetitive reporting tasks and automating them using AI-enabled tools or workflow platforms.
• Human-in-the-Loop Validation: Ensuring AI-generated outputs are reviewed, accurate, and aligned with business requirements.
• Soft Skills
• Communication: Explaining complex data findings to non-technical stakeholders.
• Collaboration: Partnering with marketing, finance, and data engineering teams.
• Problem-Solving: Identifying root causes of performance issues and recommending optimizations.
• Attention to Detail: Ensuring the accuracy and reliability of reports.
• Curiosity & Business Acumen: Proactively identifying trends and opportunities within the data.

Education

• Bachelor's degree in Business Analytics, Marketing Analytics, Statistics, Computer Science, Economics, or a related quantitative field.
• Master's degree in Data Analytics, Business Intelligence, or Marketing Analytics is a plus.
• Equivalent work experience in data analysis or marketing reporting may be considered in place of formal education.

The indicated pay range is a goodfaith estimate based on required qualifications, experience, training, and other factors permitted by law. It reflects the pay band established by the client company. Actual offers may vary depending on skills, experience, geographic location, and expected work quality. Most candidates start in the lower half of the range. Pay history is not considered where prohibited by law. This information serves as a general guideline for compensation discussions.

To support a fair and efficient hiring process, we may use artificial intelligence (AI) tools to help review applications. Our team carefully reviews all candidates, and AI is used only as a support tool-never as the sole decision-maker.