The Role

Are you passionate about advancing the data science craft and leading work that drives measurable business impact across teams? 

Join Mentimeter as a Senior Data Scientist, where you will play a pivotal role in shaping how data science supports our Enterprise go-to-market motions and helps Mentimeter make better strategic decisions.

Data is central to how Mentimeter succeeds. At Mentimeter, the Catalyst department is on a mission to realise our company strategy and drive innovation, growth, and impact throughout the company by using data, automations and generative AI. In this role, you will collaborate with cross functional teams, senior stakeholders, and company leaders to identify high impact opportunities and turn them into data science solutions that improve decision making, customer outcomes, and revenue growth.

You will join the Revenue Analytics team, working at the intersection of analytics, data science, revenue operations, and business. Your work will not only influence team and functional outcomes, but also contribute to broader cross functional goals across our go-to-market organisation.

What you’ll do

• Lead data science initiatives and workstreams for our Enterprise go-to-market motions, from opportunity discovery and problem framing through to delivery, adoption, and impact measurement.
• Design, build, and productionise machine learning models and data products such as predictive scoring, clustering, forecasting, segmentation, recommendation, and prioritisation models.
• Identify and shape high impact opportunities across retention, engagement, revenue growth, sales efficiency, customer lifecycle, and go-to-market performance.
• Partner with Revenue Operations, Product Analytics, Analytics Engineers as well as senior business stakeholders and company leaders to align priorities and drive impact.
• Set and evolve data science craft standards, including best practices for modelling, code quality, deployment, monitoring, documentation, automation, and responsible use of AI.
• Mentor and guide data scientists, analysts, and cross functional partners, helping raise the quality and impact of data science work across the function.
• Communicate recommendations and complex analyses in a way that influences decisions across different levels of the organisation.

We believe you have

• A minimum of 8+ years of relevant experience in data science, analytics, machine learning, or a closely related field.
• A proven track record of leading data science projects or workstreams end-to-end, including problem framing, stakeholder alignment, technical delivery, adoption, and impact measurement.
• Deep expertise in data science methodologies, with strong proficiency in Python, SQL, machine learning, statistics, and applied modelling.
• Experience using AI tools such as Cursor, Claude, or similar to improve productivity, automation, and delivery quality.
• Strong business acumen, with the ability to connect data science opportunities to strategic business objectives across sales, marketing, product, revenue operations, customer engagement, retention, or growth.
• Experience navigating ambiguous or complex business problems, identifying the right analytical approach, and driving alignment across multiple teams.
• Strong software and ML engineering practices, including git, code reviews, testing, versioning, monitoring, documentation, and writing performant, maintainable code for production use.
• Experience setting or improving technical standards, best practices, reusable patterns, or ways of working within a data science, analytics, or engineering team.
• Exceptional communication and stakeholder management skills, with experience in influencing senior stakeholders priorities and decisions through clear narratives, visualisations, and recommendations with clear business impact.
• A track record of mentoring others, providing technical guidance, and fostering a culture of high standards, continuous learning, and collaboration.
• Experience collaborating closely with data engineers or analytics engineers on data pipelines, model deployment, monitoring, and scalable data foundations.

Nice to have

• Familiarity with modern data tools such as Snowflake, Hex, dbt, or similar.
• Experience with cloud platforms such as AWS or Google Cloud.
• Experience working in a SaaS environment, especially with enterprise go-to-market, revenue, customer lifecycle, product usage, or retention data.
• Experience influencing company-level priorities through data science, analytics, or strategic insight work.

Not required

• Swedish is not required (as daily work is carried out in English and the Mentimeter team currently boasts 50+ different nationalities)
• A traditional cover letter is not required as part of your application

📍 Location:

This is primarily an onsite role located at Mentimeter HQ in Stockholm, with a hybrid approach and ability to work from home up to twice per week.

Please note that we do not offer visa relocation sponsorship for this position.  

💡Our recruitment process:

1. Introduction interview
2. Competence interview, including a live case.
3. Personality & Logical ability test
4. Culture interview
5. References & Offer

Compensation: 

At Mentimeter, we believe in fair and transparent compensation that grows with you.

The salary range for this role is SEK 70,000–SEK 86,000 per month. It’s intentionally broad to reflect the different stages of growth within the role: from early development to deep expertise and meaningful impact.
Where an individual is placed within the range depends on factors such as relevant experience, demonstrated skills, and alignment with the role’s requirements.

We’re committed to supporting your growth. You’ll have ongoing development conversations with your manager, and your salary will evolve as you build skills and contribute to our mission.

In addition to your monthly salary, we offer a comprehensive benefits package—learn more about it here: https://www.mentimeter.com/benefits/stockholm.