Senior Data Scientist

Senior Data Scientist

We are looking for a Senior Data Scientist to join a global technology organisation and work on machine learning solutions that directly influence customer engagement, personalisation and conversion.

You will join a cross-functional, international team responsible for building intelligent decision-making systems across customer communication and digital journeys. This is a hands-on role combining machine learning, reinforcement learning, experimentation and causal inference, with a strong focus on taking models into production and measuring their real-world impact.

You will work closely with Data Scientists, Software Engineers, Marketing Analytics and Product teams to develop scalable solutions that determine the best action, message or customer journey for each individual user.

About the role

Your work will focus on three key areas:

• Intelligent decisioning - designing and scaling machine learning and reinforcement learning solutions, including contextual bandits, to optimise communication channels such as email, SMS and push notifications.
• Personalised customer journeys - developing models that use customer behaviour, context and preferences to determine the most relevant next step in the customer funnel.
• AI-assisted content & search - building intelligent systems to index, search and retrieve marketing assets such as images and copy, as well as supporting the automated creation of high-performing communication content.

You will have a direct impact on how organisations understand customer behaviour and make data-driven decisions at scale.

What you’ll do

• Build, own and continuously improve ML and reinforcement learning models running in production.
• Develop decisioning logic that determines the best next action for users across customer journeys and communication lifecycles.
• Design and evolve contextual bandit systems, including approaches such as Thompson Sampling, offline policy evaluation and low-latency deterministic inference.
• Work closely with Engineering teams on system architecture and the integration of models into production platforms.
• Define how models make decisions, how those decisions are served at scale and how failures can be handled and rolled back safely.
• Lead experimentation for decisioning models, defining success metrics, guardrails and appropriate experimental methodologies.
• Apply rigorous statistical methods, including sequential testing, propensity methods and causal inference, to evaluate model performance.
• Monitor models in production, including performance, input-data quality, drift and latency.
• Analyse customer behaviour and translate model outputs into decisions that business and marketing stakeholders can understand and trust.
• Collaborate with Engineering, Marketing Analytics, CRM and Product teams to turn data science solutions into measurable business outcomes.

What you’ll bring

• 5+ years of professional experience in Data Science, Machine Learning or a related quantitative field.
• A proven track record of taking machine learning models from experimentation into production.
• Strong Python skills and experience working with modern ML/data platforms such as Databricks, Spark and MLflow.
• Strong knowledge of machine learning for personalisation and recommendation systems.
• Hands-on experience with reinforcement learning and/or contextual bandits, such as Thompson Sampling, epsilon-greedy approaches and reward design.
• Strong understanding of experimentation and causal inference, including designing and analysing controlled experiments in high-traffic environments.
• Experience with classical machine learning techniques such as regression, classification, clustering and recommendation systems.
• Experience working with customer behaviour data, segmentation and production feature pipelines.
• Strong statistical reasoning and the ability to evaluate model performance and experimental results accurately.
• Excellent communication skills and the ability to work effectively with technical and non-technical stakeholders.
• A pragmatic, curious and collaborative approach to problem-solving.

Nice to have

• Experience with off-policy evaluation, counterfactual learning or propensity methods.
• Knowledge of sequential testing, including SPRT.
• Experience with experimentation platforms such as Statsig or similar tools.
• Experience with streaming systems and low-latency model inference.
• Experience using unstructured data as model features, including embeddings and text signals.
• Background in marketing, CRM decisioning, customer communications or funnel/conversion optimisation.

What you can expect

• Work on large-scale machine learning systems with millions of users.
• Direct impact on personalisation, customer experience and business performance.
• Collaboration with experienced Data Scientists, Engineers, Product Managers and Analytics professionals across international teams.
• A modern technology stack and opportunities to influence ML architecture and experimentation practices.
• End-to-end ownership of projects, from problem definition and experimentation through to production and continuous optimisation.
• Exposure to advanced areas of ML, including reinforcement learning, contextual bandits, causal inference and AI-powered decisioning.
• A highly collaborative, autonomous and product-oriented working environment.
• Access to a modern office in Warsaw, with flexible employee facilities.

We are looking for someone who enjoys solving complex problems with data, is comfortable working with ambiguity and can combine strong technical expertise with a clear understanding of business and customer needs.

Even if you do not meet every requirement but have strong experience in production Data Science and believe you could thrive in this environment, we would be interested in hearing from you.