Senior Statistician – Causal Inference

Jit Team; Malmö kommun; Hybrid; SEK 62,000 - 80,000; Full time

Job summary

Jit Team is seeking a data-driven statistician to join a mature production search project with causal inference, experimental design, and ranking improvements within a global engineering environment. Hybrid work with Malmö office and relocation considerations for newcomers.

You'll work with Python/R, Solr/Lucene, and ML teams to conduct experiments, analyze user behaviour, and report findings to stakeholders. This position offers a high-impact opportunity in a fast-growing tech portfolio.

Qualifications

• MS/PhD in Statistics or related field.
• Strong expertise in causal inference and experimental design.
• Experience with A/B testing and observational studies.
• Proficiency in Python or R for analysis.
• Knowledge of IR metrics like NDCG and MRR.

Responsibilities

• Design and analyse experiments to evaluate search ranking changes.
• Apply causal inference to quantify impact on user behaviour.
• Identify biases and confounding factors in experiments.
• Analyse large-scale search logs and engagement data.
• Collaborate with ML and engineering teams to validate models.
• Present statistics to stakeholders clearly.
• Improve methodologies and validation processes.

Skills

Causal inference

Experimental design

A/B testing

Observational studies

Education

MS/PhD in Statistics/Biostatistics/Econometrics/Applied Mathematics

Tools

Python

R

Solr

Lucene

A/B Testing

Causal Inference

Bayesian Statistics

Statistical Modelling

Econometrics

NDCG

MRR

Click Models

Propensity Score Matching

Synthetic Control

Difference-in-Differences

Instrumental Variables

Job description

Salary: 5600–7200 SEK/MD on B2B

Remote: Hybrid (3 days/week in Malmö office). Commuting possible for the first 3 months; relocation to Sweden required afterwards.

Why choose this offer?

• Opportunity to work on globally used web and developer platforms
• Direct impact on 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

Project

You will join a mature, large-scale production search project combining traditional lexical search technologies (Solr/Lucene) with semantic search and machine learning-based ranking. The project focuses on improving search relevance and ranking quality through rigorous statistical analysis, causal inference, and experimentation.

You will work closely with search and ML engineering teams, designing experiments, analysing user behaviour, identifying biases, and evaluating the impact of ranking changes on production metrics. The main objective is to ensure data-driven decisions are statistically sound and supported by reliable evidence.

Responsibilities you'll have

• Design and analyse experiments (A/B testing, interleaving, quasi-experiments) to evaluate search ranking and relevance changes.
• Apply causal inference methods to identify the real impact of ranking changes on user behaviour and search performance.
• Identify and address confounding factors, selection bias, and other statistical issues affecting experimental results.
• Analyse search and user engagement data to distinguish genuine improvements from noise, seasonality, and measurement biases.
• Develop and validate statistical models of user behaviour, including click models, exposure models, and position bias correction.
• Collaborate with ML and Search Engineers to evaluate model performance and support data-driven decisions.
• Communicate statistical findings, uncertainty, and limitations clearly to technical and business stakeholders.
• Improve experimentation methodologies, metric definitions, and statistical validation processes.

Expected competences and knowledge

• Advanced degree (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 modelling, including hypothesis testing, regression analysis, variance estimation, and Bayesian methods.
• Experience designing and analysing A/B tests, interleaving experiments, and observational studies.
• Knowledge of causal inference techniques, such as Difference-in-Differences, Instrumental Variables, Propensity Score Matching, Synthetic Control, and Uplift Modelling.
• Experience analysing large-scale behavioural or observational data, such as search logs, clickstream, and user engagement data.
• Understanding of statistical biases, including position bias, selection bias, confounding, and feedback loops.
• Ability to quantify uncertainty, validate statistical assumptions, and interpret experimental results.
• Proficiency in Python or R for statistical analysis and independent data exploration.
• Excellent communication skills and ability to explain complex statistical concepts to non-technical stakeholders.

Additional Advantages

• Experience in search, recommendation systems, or online marketplaces.
• Familiarity with Information Retrieval metrics, such as NDCG and MRR.
• Experience with click models, exposure models, and position bias correction.

Technologies you'll work with

• Python
• R
• Solr
• Lucene
• A/B Testing
• Causal Inference
• Bayesian Statistics
• Statistical Modelling
• Econometrics
• NDCG
• MRR
• Click Models
• Propensity Score Matching
• Synthetic Control
• Difference-in-Differences
• Instrumental Variables

Client – why choose this particular client from the Jit portfolio?

Our client is a global technology company known for building innovative digital products and delivering exceptional user experiences at scale. The organization creates solutions used daily by millions of users around the world and invests heavily in engineering excellence, product innovation, and modern technologies. This project offers the opportunity to work on highly impactful developer-facing platforms while collaborating with experienced international teams. It is an ideal environment for engineers who enjoy solving complex technical challenges and contributing to products with global reach.

About Jit Team

The Human Factor of IT - it’s not just a slogan, it’s a philosophy. The foundation of Jit Team is people, which is why we prioritise you. We employ over 770 experienced experts, to whom we offer developmental projects, a wide range of benefits, and a proprietary professional development programme. Together with clients from around the world, we create innovative IT solutions delivered by highly specialised and efficient teams.

Behind our maxim are also charitable and educational activities. We support schools, universities, and educational institutions by conducting workshops, running educational projects, sponsoring events, and donating learning equipment. We offer internships that help launch careers in IT. We support water rescuers and hospitals by providing the necessary equipment. We also support numerous charitable organisations helping people in need, children, and the elderly. We are a Polish company and we share what we have achieved over more than 15 years of activity. By supporting local initiatives, we contribute to the circulation of good energy.