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Open nowPosted 9 hours ago

Apple - Junior Statistician / Causal Inference Scientist — Search Relevance & Ranking

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Your applicationOpen nowApple - Junior Statistician / Causal Inference Scientist — Search Relevance & RankingJit
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The clock on this job

Early applications get read.

13.3% of postings close within 7 days. Measured by our own scanner across the market. Jit postings stay open a median of 5 days.

Share of postings closed within
  1. 2.1%1 day
  2. 4.6%3 days
  3. 13.3%7 days
  4. 21.3%14 days
  5. 35.7%30 days
  6. 59.1%60 days
This job: posted 9 hours ago

Jit median: 5 days open

The posting

Salary: 3200–4400 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 large-scale production search project combining traditional lexical search (Solr/Lucene) with semantic search and machine learning-based ranking. Working alongside experienced statisticians and search/ML engineers, you will help analyse ranking performance, evaluate experiments, identify statistical biases, and understand the impact of changes on search relevance and user behaviour.

The role offers an opportunity to apply academic knowledge of statistics, experimental design, and causal inference to real-world production data, while developing practical skills under the guidance of senior team members.

Responsibilities you'll have

  • Support the design and analysis of experiments (A/B testing, interleaving) to evaluate search ranking and relevance changes.
  • Assist in applying causal inference methods to observational search and user engagement data.
  • Help identify confounding factors, selection bias, seasonality, and novelty effects in experimental results.
  • Perform statistical analyses of experiment and search log data, including hypothesis testing, regression, and variance estimation.
  • Contribute to offline evaluation activities, including click models, exposure models, and position-bias correction.
  • Document analytical findings, assumptions, and statistical limitations.
  • Communicate results clearly to engineering and product teams.
  • Learn and apply experimentation methodologies and statistical validation practices under the guidance of senior team members.

Expected competences and knowledge

  • Degree (BS/MS) in Statistics, Biostatistics, Econometrics, Applied Mathematics, or a related quantitative field.
  • Good understanding of statistical fundamentals, including hypothesis testing, regression analysis, and variance estimation.
  • Academic knowledge of causal inference and experimental design, including potential outcomes and Directed Acyclic Graphs (DAGs).
  • Understanding of bias and confounding in observational data.
  • Basic experience with Python or R for statistical analysis and data exploration.
  • Ability to analyse real-world datasets and interpret statistical results.
  • Strong analytical thinking and problem-solving skills.
  • Ability to document findings, explain statistical concepts, and communicate analytical results clearly.
  • Eagerness to learn, receive feedback, and develop statistical expertise in a collaborative environment.

Additional advantages

  • Academic projects, internships, or research involving A/B testing, experimentation, or causal analysis.
  • Familiarity with search and recommendation systems and ranking metrics such as NDCG and MRR.
  • Knowledge of click models, exposure models, and position bias.
  • Exposure to causal inference tools such as DoWhy, EconML, or CausalImpact.
  • Previous internship or part-time experience in search, recommendation, or marketplace environments.

Technologies you'll work with

  • Python
  • R
  • Solr
  • Lucene
  • A/B Testing
  • Causal Inference
  • Statistical Modelling
  • Regression Analysis
  • Bayesian Statistics
  • NDCG
  • MRR
  • DoWhy
  • EconML
  • CausalImpact

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.

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