Data Scientist

About the Team:

At Typeform, the Data & Insights team’s charter is to make data actionable through multiple mediums—reports, dashboards, AI/ML-models—that help us fuel growth and drive efficiencies within our business. Within that charter, our Data Science practice focuses on building cutting-edge machine learning capabilities that help revolutionize how we leverage data and empower our customers to collect information in a conversational and personalized way.

About the Role:

As a Data Scientist at Typeform, your mission will be to analyze data, build models, and prototype innovative AI features. You will partner closely with Product, R&D, and GTM teams to scope problems, explore data, and deliver ML-powered solutions that are both technically sound and business-relevant. This is a hands-on role with a strong mandate for innovation, experimentation, and delivering production-ready solutions that drive real impact.

Things you’ll do:

AI Feature Development & Evaluation:

• Partner with Engineering to design and implement AI-powered product features, applying best practices around model selection, system design, optimization, and monitoring.
• Evaluate LLM and generative AI features using both quantitative metrics and qualitative techniques—developing benchmarks, stress tests, and custom evaluation pipelines to ensure reliability and performance.

Innovation & Research:

• Stay on top of emerging methods and tools in ML, deep learning, NLP, and agentic workflows—bringing new ideas to the table and pushing the envelope of what’s possible.
• Contribute to internal knowledge sharing and cross-functional learning through documentation, demos, and collaborative experimentation.

Ideation & Scoping:

• Collaborate with stakeholders across R&D (Product, Engineering, Research, Design) and GTM to frame analytical problems, align on objectives, and define success metrics.
• Translate ambiguous business challenges into clearly scoped, feasible data science projects.

Data Exploration & Analysis:

• Conduct exploratory data analysis (EDA) to surface trends, patterns, outliers, and opportunities for impact.
• Work with Analytics Engineering and Data Engineering teams to source and validate high-quality data for model development.

What you already bring to the table:

• 3–5+ years of experience in data science, ML, or applied statistics in a product or growth-oriented B2B SaaS environment.
• Experience collaborating closely with Product, Engineering, or Marketing teams to ship user-facing AI features or data products.
• Ability to clearly communicate technical concepts to stakeholders across varying levels of technical fluency.
• Strong programming skills in Python and experience with ML libraries like scikit-learn, XGBoost, PyTorch, or TensorFlow.
• Demonstrated ability to design, train, and validate models using structured and unstructured data.
• Strong analytical skills and experience working with large datasets using SQL, Pandas, and other data tools.

Extra awesome:

• Experience with LLMs, embeddings, and vector search tools (e.g. LangChain, OpenAI APIs, Pinecone, FAISS).
• Familiarity with agentic AI workflows, prompt engineering, or RAG (Retrieval-Augmented Generation) pipelines.
• Experience building evaluation pipelines for ML and AI models.
• Previous experience working in cross-functional environments and driving ML/AI projects from ideation to deployment.
• Comfort using tools like Jupyter, Looker, GitHub, or cloud platforms (AWS, GCP).