Marketing Data Scientist

Jobicy; United States; Remote; USD 120,000 - 160,000; Full time

Job summary

Vonage is seeking a Data Scientist to own demand and revenue intelligence, sitting at the intersection of marketing strategy and commercial outcomes. You will build predictive models and analytical frameworks that reveal growth sources before they arrive and shape how audiences are reached and channels invested in.

You will work with Salesforce and Snowflake data, develop forecasting methodologies, and translate complex outputs into actionable narratives for executives, accelerating pipeline

Qualifications

• 8+ years of experience in Data Science, Revenue Analytics, or a related field.
• Salesforce data experience across Leads, Contacts, Accounts, Opportunities, Campaigns.
• Snowflake data warehouse experience including SQL-based modeling.
• Experience modeling pipeline generation, conversion rates, and revenue velocity across the full funnel.

Responsibilities

• Analyze and model the relationship between marketing investment, channel performance, and revenue outcomes.
• Design and maintain reporting views and self-serve analytics assets for internal stakeholders.
• Identify high-value market segments and audiences through data modeling.
• Develop personalization models for tailored customer experiences across channels.
• Collaborate with Marketing and Sales to define forecasting methodologies and embed models into workflows.
• Translate model outputs into clear narratives for executives.
• Contribute to AI-ready data structures in Snowflake for marketing automation inputs.

Skills

Data storytelling

Business acumen

Forecasting

Self-starter

AI literacy

Education

Master’s or PhD in Statistics / Economics / CS

Tools

Salesforce

Python

SQL

Tableau / Power BI

Marketing automation platforms

Snowflake / Cloud platforms

Git

Excel / Google Sheets

Job description

Why this role matters:

We are looking for a Data Scientist to own our demand and revenue intelligence capabilities. You will sit at the intersection of marketing strategy and commercial outcomes, building the predictive models and analytical frameworks that tell us where growth is coming from before it arrives. Your work will directly shape how we reach the right audiences, invest in the right channels, and accelerate pipeline - turning marketing activity into a measurable, forward-looking revenue engine.

Your key responsibilities:

• Analyze and model the relationship between marketing investment, channel performance, and revenue outcomes, connecting spend to growth
• Design and maintain reporting views and self-serve analytics assets for internal stakeholders and marketing partners; making model outputs and performance data accessible, consistent, and actionable across teams
• Identify high‑value market segments and audiences through data modeling to inform how and where we compete
• Develop personalization models and frameworks that enable tailored customer experiences across channels, from dynamic content and offers to next-best-action recommendations
• Collaborate with Marketing and Sales teams to define forecasting methodologies and embed models into operational workflows
• Translate complex model outputs into clear, actionable narratives that drive strategic decisions at the executive level
• Contribute to the development of AI‑ready data structures in Snowflake, including clean feature tables, scoring outputs, and audience segments that serve as reliable inputs for marketing automation and AI‑driven decisioning

What you’ll bring:

• Strong understanding of the full B2B revenue funnel - from awareness and demand generation through pipeline to closed revenue - and how data flows across it
• Strong business acumen with the ability to connect predictive model outputs to strategic marketing and revenue decisions
• The ability to influence RevOps, Sales, and Marketing stakeholders through data‑led storytelling
• A rigorous yet pragmatic approach to forecasting - knowing when to build a sophisticated model and when a well‑structured regression is enough
• A proven self‑starter comfortable operating in fast‑moving, commercially‑driven environments
• A working fluency with AI tools and LLM‑based workflows - able to leverage AI to accelerate analysis, prototype models, and operate effectively in an AI‑first data environment

Required:

• 8 years of experience in Data Science, Revenue Analytics, or a related field
• Salesforce data experience: proven hands‑on experience with Salesforce data across the full object model (Leads, Contacts, Accounts, Opportunities, Campaigns), and a deep understanding of how marketing and sales data interconnects within Salesforce
• Snowflake data warehouse experience: demonstrated experience querying, modeling, and working with data in Snowflake, including SQL‑based data modeling and working with structured analytical data sets
• Experience modeling pipeline generation, conversion rates, and revenue velocity across the full funnel

Tools & Technologies:

• Salesforce - full object model (Leads, Contacts, Accounts, Opportunities, Campaigns), SOQL, Salesforce administration, Salesforce Einstein Analytics / Tableau CRM
• Python - scikit‑learn, statsmodels, Prophet, pandas, NumPy for forecasting and modeling
• SQL - advanced querying across CRM and marketing data sources
• Data Visualization - Tableau, Power BI, Salesforce‑native dashboarding
• Marketing Automation Platforms - Marketo, HubSpot, or Pardot (data structure familiarity)
• Cloud Data Platforms - Snowflake, AWS, GCP, or Azure for data extraction and model deployment
• Version Control - Git/GitHub or GitLab
• Spreadsheet & Presentation Tools - Excel, Google Sheets for stakeholder‑facing outputs

What we consider a plus:

• Experience with customer lifetime value (LTV) modeling and churn prediction
• Familiarity with marketing automation platforms and how they feed into Salesforce (e.g., Marketo, HubSpot)
• Experience with lead‑to‑revenue funnel analytics in a B2B SaaS environment
• Working knowledge of digital marketing platforms and their underlying data structures
• Advanced degree (Master’s or PhD) in a quantitative field such as Statistics, Economics, or Computer Science

Disclaimer:

The posted range represents the good faith salary for this role at the time of posting. Final compensation is determined by factors including (but not limited to) geographic location, relevant experience, specific skill sets, and internal equity.

There’s no perfect candidate. You don’t need all the preferred qualifications to make a valuable impact on our team. Our employees and customers come from diverse backgrounds, so if you’re passionate about what you could achieve at Vonage, we’d love to hear from you.

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Who we are:

Vonage is a global cloud communications leader. And your talent will further help brands - such as Airbnb, Viber, WhatsApp, and Snapchat - accelerate their digital transformation through our fully programmable‑based unified communications, contact center solutions, and communications APIs. Ready to innovate? Then join us today.

Note: The purpose of this profile is to provide a general summary of essential responsibilities for the position and is not meant as an exhaustive list. Assignments may differ for individuals within the same role based on business conditions, departmental need or geographic location.