Senior Statistician (Causal Inference)

Quick Facts

• Role: Senior Statistician (Causal Inference)

• Work setup: Hybrid (3 days/week in Malmö office); commuting possible for first 3 months, then relocation to Sweden required

• Work domain: Production search combining lexical search with semantic/ML ranking

Description

You will join a large-scale production search project that improves search relevance and ranking quality through rigorous statistical analysis, causal inference, and experimentation.

You will design experiments, analyze user behavior, identify biases, and evaluate the impact of ranking changes using reliable, statistically sound evidence.

The goal is to support data-driven decisions with clear communication of findings and uncertainty.

Responsibilities

• Design and analyze experiments (A/B testing, interleaving, quasi-experiments) to evaluate ranking and relevance changes

• Apply causal inference methods to measure real impact of ranking changes on user behavior and search performance

• Identify and address confounding factors, selection bias, and other statistical issues

• Analyze search and user engagement data to separate genuine improvements from noise, seasonality, and measurement bias

• Develop and validate statistical models of user behavior (click models, exposure models, position bias correction)

• Collaborate with ML and Search Engineers to evaluate model performance and support data-driven decisions

• Communicate statistical findings, uncertainty, and limitations to technical and business stakeholders

• Improve experimentation methodologies, metric definitions, and statistical validation processes

Requirements

• MS/PhD (or equivalent experience) in Statistics, Biostatistics, Econometrics, Applied Mathematics, or a related quantitative field

• Strong expertise in causal inference, experimental design, and quasi-experimental methods

• Solid understanding of statistical modeling (hypothesis testing, regression analysis, variance estimation, Bayesian methods)

• Experience designing and analyzing A/B tests, interleaving experiments, and observational studies

• Knowledge of causal inference techniques (Difference-in-Differences, Instrumental Variables, Propensity Score Matching, Synthetic Control, Uplift Modeling)

• Experience analyzing large-scale behavioral/observational data (search logs, clickstream, user engagement data)

• Understanding of statistical biases (position bias, selection bias, confounding, feedback loops)

• Ability to quantify uncertainty, validate assumptions, and interpret experimental results

• Proficiency in Python or R for statistical analysis and data exploration

• Excellent communication skills for non-technical stakeholders

Benefits

• Salary: 5600–7200 SEK/month on a B2B basis

• Opportunity to work on globally used web and developer platforms and directly influence frontend architecture, APIs, and developer-facing solutions

• Collaboration with international, cross-functional engineering and product teams

• Work on large-scale mapping and location-based technologies used worldwide