Staff Applied Scientist (Marketing)

Quick Facts

• Role: Staff Applied Scientist (Marketing)

• Focus: Applied AI and experimentation to improve marketing acquisition, conversion, and customer value

Description

Turn open-ended marketing questions into experiments, models, and production AI workflows that drive measurable business results. Define the scientific approach under uncertainty by investigating data, building hypotheses, training and evaluating models, and designing tests for incremental impact. Partner with engineers to deploy, monitor, and iterate models, ensuring reliability, privacy, and adoption.

Responsibilities

• Partner with Marketing, Product, and Engineering to identify high-value opportunities and translate problems into testable hypotheses with clear success metrics.

• Develop AI workflows for audience understanding, personalization, recommendations, campaign optimization, and content generation.

• Design controlled experiments and apply causal methods when randomization is impractical to measure incremental improvements.

• Train, adapt, and evaluate models for marketing tasks; compare baselines, predictive models, and LLM-based approaches.

• Build reliable training/evaluation datasets while handling missing data, selection bias, imbalance, and preventing leakage.

• Create repeatable evaluation frameworks linking model performance to marketing decisions and customer outcomes, including factual accuracy tests for generative work.

• Own scientific outcomes through production rollout and adoption: deploy, monitor, diagnose regressions, and improve latency/cost with feedback loops and versioning.

• Stay current with AI advances, document experiments, and share reusable methods and trade-offs.

Requirements

• Proven applied science/ML track record defining problems under uncertainty and moving models from experimentation into sustained business use.

• Strong statistics, machine learning, and experimental design skills, with depth in causal inference and/or marketing science/personalization/optimization; ability to identify bias and quantify uncertainty.

• Hands-on experience building models for customer behavior or marketing decisions and applying AI in business workflows.

• Strong Python and SQL skills; experience with PyTorch (or equivalent) and ability to write tested, maintainable, reproducible code.

• Experience with customer/product/campaign data and limitations of observational evidence; ability to choose metrics and connect offline results to business impact.

• Judgment on AI reliability and sensitive data, including mitigation for unsupported outputs, prompt injection, and data exposure.

• Ability to work autonomously: prioritize experiments, make practical trade-offs, and communicate clearly in English.

• Master’s or PhD in CS/ML/Statistics (or related) or equivalent experience with comparable scientific depth.

Benefits

• Competitive compensation (34,000–47,000 PLN/month), stock options, and annual bonus.

• Flexible benefits allowance.

• City-center office and friendly, non-corporate atmosphere.

• Real ownership and visible impact.