Marketing Data Scientist
Vonage is hiring a Marketing Data Scientist. Level rates it ; you can apply on Vonage.
Level's read on this job
- On Level's scale, this data scientist role is Uses AI ●●○○: an ordinary role that requires AI tools.
- The posting mentions scikit-learn, Snowflake and data science among its tools and skills.
- Level classes it as a senior role.
- Vonage has 22 other open roles on Level.
AI in this role
Marketing Data Scientist needed to build predictive models, revenue intelligence capabilities, and leverage AI tools for marketing automation.
Join Vonage and help us innovate cloud communications for businesses worldwide!
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
#LI-JS3
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.
To learn how we process your personal data during the recruitment process, please refer to our Privacy Notice.
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.
How we rate this
Marketing Data Scientist at Vonage rates 50 out of 100 for how much of the daily work is AI. That makes it Uses AI (AI Level 2 of 4). The level is about AI in the job, not seniority.
Uses AI. An ordinary role that requires AI tools.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Also common in data scientist jobs at this level
Pay
- Typical data scientist job
- $166k
This posting doesn't list pay. Use the typical data scientist figure when pay comes up. See data scientist jobs
Questions you could be asked
- Tell me about a project where data science was part of your work. What did you do?
- Tell me about a project where predictive modeling was part of your work. What did you do?
- Tell me about a project where marketing analytics was part of your work. What did you do?
- Tell me about a project where sql was part of your work. What did you do?
- Tell me about a project where forecasting was part of your work. What did you do?
Adapt your resume
- List these exact terms on your resume: Data Science, Predictive Modeling, Marketing Analytics, SQL, and Forecasting. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Put the AI tool in a bullet point about what you did, not just in a skills list. This role treats it as a required part of the job.
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