Senior Data Scientist/ML Engineer
At Campaignswell, we're revolutionizing marketing analytics with our AI-powered predictive platform tailored for apps, games, and e-commerce businesses. Our cutting-edge technology delivers precise lifetime value (LTV) predictions within hours, empowering clients to scale their advertising efforts confidently. By seamlessly integrating product and marketing analytics into a unified dashboard, we provide actionable insights that drive growth and profitability. Founded in 2023 and headquartered in San Francisco, our dynamic team is committed to transforming the marketing landscape through innovation and data-driven strategies.
We're looking for a Senior Data Scientist/ML Engineer who's excited to build models that ship, not just models that impress.
This is a senior individual contributor role sitting at the intersection of data science and engineering. You'll design and deliver machine learning solutions that directly power Campaignswell's product, from revenue prediction, and probabilistic attribution to internal tooling that makes our analysts faster and smarter. You'll work closely with Product and Analytics, and have real ownership over the ML roadmap. We're at a stage where the right person can shape how we do this, not just inherit someone else's decisions.
- Design, build, and deploy ML models into production from problem framing through to monitoring and iteration.
- Develop predictive features for the Campaignswell platform (e.g. revenue forecasting, probabilistic attribution, audience segmentation, anomaly detection).
- Collaborate with Product and Engineering to define how ML capabilities are surfaced to customers.
- Build and maintain scalable ML infrastructure and pipelines in close partnership with the data engineering team.
- Establish best practices for model evaluation, versioning, and monitoring.
- 4+ years of experience in data science or ML engineering, with a strong track record of shipping models to production.
- Proficiency in Python and the core ML stack (frameworks of gradient boosting, NN).
- Solid understanding of MLOps principles you care about how models behave after they're deployed, not just how they perform in a notebook.
- Experience with cloud platforms (AWS) and modern data infrastructure (dbt, Snowflake, Airflow, or similar).
- Strong statistical foundations, you know when to use a simple model and when complexity is justified.
- Clear communicator who can explain trade-offs to engineers and business stakeholders alike.
- Experience with AI tools - not just to tick a box, but to genuinely work faster and better.
- English level: B1.
- Experience in marketing analytics, adtech, or multi-touch attribution.
- Familiarity with LLMs and experience building or fine-tuning models for applied NLP tasks.
- Prior experience in a high-growth SaaS environment.
- Competitive salary.
- Fully remote with flexible working hours.
- Home office stipend and learning & development budget.
- 21 paid vacation days.
- Regular team offsites and a culture that actually lives its values.
Campaignswell is an equal opportunity employer. We celebrate diversity and are committed to building an inclusive team. If you're passionate about helping brands grow through smarter data and love collaborating across disciplines to deliver impact, we’d love to hear from you!
