The Content team is looking for a talented, versatile Marketing copywriter to craft the short-form copy that fuels Vonage's marketing engine. This person writes the words that make people stop, click, register, and convert — from a subject line to a campaign landing page, a digital ad to an event booth headline.

A sharp, instinctive communicator, this role will work across Marketing functions and teams to produce high-quality, on-brand copy across all marketing channels. They bring an editorial eye, a keen awareness of the market, and a performance mindset.

What You’ll Do

• Write clear, compelling, on-brand short-form copy across a full range of marketing formats including infographics, emails, digital ads, web pages, pitch decks, interactive content, event copy, CTAs, podcast scripts, and promotional materials
• Collaborate closely with cross-functional teams to deliver copy that supports integrated marketing campaigns, events, announcements, product launches, and go-to-market strategies
• Translate creative and campaign briefs into compelling copy that speaks to target audiences and drives desired actions
• Adapt tone, style, and messaging for different audiences, channels, and funnel stages — from awareness to conversion 
• Ensure all copy is consistent with Vonage brand voice, messaging hierarchy, and style guidelines
• Partner with designers to develop copy-design concepts that work together as a unified creative unit
• Manage multiple concurrent projects in a fast-paced environment, delivering on time and within scope 
• Incorporate feedback from stakeholders efficiently, balancing creative integrity with business requirements
• Maintain awareness of copy performance and apply learnings to improve future work

What You’ll Bring

• 5-7 years of experience writing short-form marketing copy in a B2B environment, preferably supporting a SaaS, cloud, or technology brand
• A portfolio demonstrating exceptional copy across multiple formats
• A sharp editorial instinct: you know when a headline lands and when it doesn't
• Ability to write clearly about technical products and complex topics without losing the reader
• Experience working across multiple stakeholders and translating briefs into polished, campaign-ready copy
• Strong project management skills; comfortable prioritizing across a high volume of concurrent requests
• Collaborative spirit and comfort operating in a matrixed organization
• Curiosity about performance data and an eagerness to optimize copy based on results
• Working knowledge of SEO principles and emerging AEO practices (writing for AI-generated answers and LLM visibility) a plus

Application Requirements

• 5–7 years of copywriting or content marketing experience, preferably in B2B technology, SaaS, or cloud
• Bachelor's degree or higher, preferably in English, Communications, Journalism, or Marketing
• Writing portfolio or samples demonstrating short-form marketing copy (emails, ads, landing pages, web)
• Strong command of grammar, style, and tone — with an ability to adapt across audiences and channels
• Familiarity with project management tools such as Monday.com a plus
• Knowledge of the business communications, CPaaS, or enterprise software market a plus

How you’ll benefit

• Company Bonus or Commission Structure (depending on the role)
• Medical, Dental, and Vision Coverage Options
• 401(k) Savings Plan
• Company-Paid Basic Life and AD&D Insurance
• Short-Term Disability (STD)
• Long-Term Disability (LTD)
• Maternity/Parental Leave
• Flexible Spending Accounts (FSA)
• Health Savings Account (HSA)
• Employee Support Program (EAP)
• Voluntary Supplemental Insurance
• Lifestyle Benefits
• Volunteer Time Off (VTO)
• Tuition Reimbursement - available for select positions; full details will be shared during the interview process
  #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.

Why this role matters:

We are looking for a Data Scientist who speaks the language of both data and AI - and knows how to make them work together. You will serve as the critical bridge between our Snowflake data platform and the AI-powered systems that drive our marketing and go-to-market motions. Your work will ensure that our data is shaped, structured, and ready to power the next generation of agentic AI applications, enabling autonomous, intelligent systems that act on behalf of our teams and customers.

Your key responsibilities:

• Collaborate closely with the Snowflake engineering team to define, spec, and validate data requirements for models and AI applications
• Serve as the translation layer between data engineering and AI/ML teams, ensuring data is structured, clean, and optimized for downstream use
• Enable and support agentic AI workflows by designing and maintaining the data layers that power agent memory, context retrieval, and tool-use
• Build and maintain data models and transformation logic on top of Snowflake to support predictive and generative AI use cases
• Identify and resolve data quality issues in collaboration with the engineering team
• Partner with marketing science and analytics teams to ensure data assets are accessible and model-ready
• Automate and streamline data validation processes to improve reliability of AI-facing data pipelines

What you'll bring:

• Deep fluency in Snowflake - comfortable living in it daily as a power user, and confident enough to hold technical conversations with Snowflake engineers
• A strong understanding of how data must be structured and governed to reliably power AI and machine learning systems
• The ability to translate business and modeling needs into precise, actionable data requirements for engineering teams
• A collaborative mindset with the ability to operate effectively across data engineering, AI, and marketing science functions
• A proactive, self-starter approach capable of navigating ambiguous data environments and proposing pragmatic solutions

Required:

• 8 years of experience in Data Science or a data engineering-adjacent role
• Advanced proficiency in Python and SQL
• Deep expertise in Snowflake - including data modeling, Snowpark, and advanced querying
• Approximately 2 years of hands-on experience powering agentic AI workflows with data (e.g., RAG pipelines, structured data for LLM tool-calling, agent memory and context layers)
• Familiarity with vector databases or embedding-based retrieval systems (e.g., Pinecone, Weaviate, pgvector)
• Experience collaborating with or working closely alongside data engineering teams
• Familiarity with cloud data platforms (AWS, GCP, or Azure)

Tools & Technologies:

• Snowflake - Snowpark, dynamic tables, advanced SQL querying, data modeling
• Python - pandas, NumPy, SQLAlchemy, Jupyter
• LLM & Agentic AI Frameworks - LangChain, LlamaIndex, AutoGen, or similar
• Vector Databases - Pinecone, Weaviate, pgvector, or Chroma
• Cloud Platforms - AWS (S3, Lambda, SageMaker), GCP (BigQuery, Vertex AI), or Azure equivalents
• Orchestration & Pipeline Tools - dbt, Apache Airflow, or Prefect (as a collaborator/power user)
• Version Control - Git/GitHub or GitLab
• Data Quality & Observability - Monte Carlo, Great Expectations, or similar
• API & Integration Tools - REST APIs, Webhooks, JSON/YAML fluency for connecting data to AI systems

What we consider a plus:

• Experience with orchestration tools such as dbt, Airflow, or similar
• Exposure to marketing data ecosystems (CDP platforms, ad platform data structures)
• Experience in a B2B SaaS environment
• Advanced degree (Master's or PhD) in a quantitative field such as Computer Science, Statistics, or Data Engineering

#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.

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:

• Build and deploy demand forecasting and pipeline prediction models that project revenue outcomes at the campaign, segment, and market level
• Develop and maintain lead scoring, audience propensity, and opportunity scoring models to sharpen targeting and prioritize sales and marketing effort
• Analyze and model the relationship between marketing investment, channel performance, and revenue outcomes, connecting spend to growth
• 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
• Own and shape the revenue data ecosystem, ensuring data integrity, influencing how data is captured, and making it model-ready across systems
• 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

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
• Intuition for how marketing programs, channels, and audiences translate into commercial outcomes
• 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

Required:

• 8 years of experience in Data Science, Revenue Analytics, or a related field
• Proven experience building predictive and demand forecasting models tied to revenue outcomes
• Strong understanding of CRM data ecosystems and how marketing and sales data interconnects - Salesforce experience strongly preferred
• Strong proficiency in Python and SQL
• Experience modeling pipeline generation, conversion rates, and revenue velocity across the full funnel
• Proficiency with data visualization tools (Tableau, Power BI, or similar)

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.