Solutions Marketer, Competitive Intelligence
Job description
About the role
The role defines how Lovable tracks, understands, and wins against competitors through research and field-facing content. It shapes external positioning in fast-moving competitive conversations for a high-growth European company.
Data roles turn raw information into decisions. Analysts query databases and build dashboards. Data scientists build models that predict outcomes. Data engineers build the pipelines that move and store data. All three work closely with business teams and need a mix of statistics, coding, and communication. Nearly every modern company runs on data teams, from startups to banks. A strong portfolio of past analyses matters more than degrees in many hiring decisions.
Key facts
What you'll do
Competitor launches are assessed for implication, and updated positioning and guidance are delivered to the field without delay.
Content for sales assets, pitch narratives, and persona priorities is created to support the solutions marketing needs beyond competitive work.
External claims about competitors and products are sourced, verified, and held to a high bar to ensure customer safety and accuracy.
Requirements
The posting states a bachelor's degree requirement. You bring 8+ years of experience in competitive intelligence, market intelligence, product marketing, strategy, consulting, or a related field in B2B SaaS, developer tools, or AI.
You follow the AI and software creation landscape closely enough to form a clear point of view on its direction.
You have produced competitive and sales-facing content that was used in real deals under real deadlines.
You turned competitive analysis into recommendations that leadership acted on to influence decisions.
You maintain a high bar for accuracy by sourcing, dating, and verifying every claim and retiring outdated talking points.
You write clearly for both technical and executive audiences without losing precision or detail.
Practical notes
All application materials are in English, which is the company language for interviews and collaboration.
Candidates are evaluated equally, and interested applicants should use the careers portal to submit their materials.
Typical interview steps
Data interviews commonly include a SQL or coding exercise, a statistics question, and a case study. Candidates may be asked to design a metric, interpret an experiment, or build a small model. Some companies give a take-home analysis. Expect questions about past projects and the business impact of your work. Interviewers often evaluate how you communicate uncertainty and business impact, not only the math. Bringing a clean write-up of a past analysis to the interview is well received.
Good to know
Work in this area relies on tools for tracking competitors, analyzing product features, and creating sales and research content.
Roles in competitive intelligence require judgment on claims, sourcing discipline, and comfort with fast-moving market information.
Writing for technical and executive readers is a common expectation in solutions and product marketing.
Owning a research cadence and a single source of truth helps align sales, product, and leadership around competitive decisions.
Questions to ask
Good questions to ask the employer in the interview: what does success look like in the first six months, how is the team structured, what is the current biggest challenge, and how are decisions made. Asking about growth paths and the review process is also well received. Employers expect questions, and good ones show preparation.
Career growth
Data careers grow toward senior analyst, staff data scientist, or data engineering lead. Many professionals specialize in machine learning, analytics, or infrastructure. Cross-functional work with product and engineering teams becomes more important at senior levels. The field changes quickly, so continuous learning is part of the job. Professionals who can translate numbers into decisions tend to advance fastest.
About the company
Lovable is an AI-powered full-stack development platform that turns natural language prompts into production-ready web applications. The platform enables rapid prototyping and deployment.