Data Scientist

Mayflower is a technology company building highload products used by millions of people worldwide. Operating at the scale of one of the world's top-50 websites, we solve complex engineering challenges and create solutions that power real-time entertainment for a global audience.

Now we look for a Data Scientist to join our ML team

Job Responsibilities

- Search & Retrieval

- Develop and improve retrieval pipelines for large-scale production search systems.

- Work on candidate generation, query processing, matching, filtering, and retrieval strategies.

- Improve search relevance, result coverage, and overall SERP quality.

- Analyse failed searches, irrelevant results, zero-result queries, and other search-quality issues.

- Explore lexical, semantic, behavioural, hybrid, and vector search approaches.

- Ranking & Relevance

- Build, train, and optimise ranking models for search and recommendation systems.

- Develop learning-to-rank solutions using behavioural, content-based, contextual, and real-time features.

- Design ranking features based on clicks, conversions, popularity, freshness, availability, and user behaviour.

- Evaluate ranking quality using Precision, Recall, NDCG, MAP, MRR, and related relevance metrics.

- Optimise models for low-latency inference and investigate relevance degradation, bias, and feedback loops.

- Recommendation Systems

- Develop recommendation models and candidate-generation strategies for personalised and non-personalised scenarios.

- Build recall and ranking stages for multi-stage recommendation pipelines.

- Work on related-item, complementary-item, next-action, and behavioural recommendation use cases.

- Develop user, item, session, and contextual representations.

- Balance relevance, diversity, novelty, coverage, and business constraints.

- Experimentation & Evaluation

- Design and run offline and online experiments for search, ranking, and recommendation improvements.

- Build evaluation frameworks that connect model quality with product and business outcomes.

- Design and analyse A/B tests using CTR, conversion, engagement, retention, and revenue-related metrics.

- Create reproducible pipelines for data preparation, model training, evaluation, and comparison.

- Evaluate model robustness across traffic segments, query groups, user cohorts, and edge cases.

- ML Pipelines & Collaboration

- Build end-to-end ML pipelines for feature generation, training, validation, deployment, and monitoring.

- Work with high-load, real-time, and low-latency production systems.

- Process large datasets using Python, SQL, batch pipelines, streaming systems, and Kafka.

- Collaborate with product, backend, data engineering, and MLOps teams to productionise ML solutions.

- Communicate technical decisions, experiment results, and trade-offs while contributing to ML best practices.

Requirements

You’ll thrive here if you have; Strong hands-on experience building production search, ranking, or recommendation systems.; Strong Python and SQL skills for machine learning, data processing, and analytical queries.; Practical experience with learning-to-rank, candidate retrieval, search relevance, or recommender-system modelling.; Experience building and evaluating multi-stage retrieval and ranking pipelines.; Strong understanding of search and recommendation metrics, including Precision, Recall, NDCG, MAP, MRR, CTR, and conversion.; Experience with feature engineering and behavioural data such as impressions, clicks, sessions, and conversions.; Experience with ML libraries such as scikit-learn, XGBoost, LightGBM, CatBoost, PyTorch, or TensorFlow.; Experience working with large-scale production systems, distributed data processing, analytical databases, and streaming platforms.; Strong understanding of experimentation and A/B testing, with the ability to independently build, and validate ML solutions.; That can be a plus:; Experience with Elasticsearch, OpenSearch, Solr, Lucene, or another search-engine stack.; Experience with vector databases, approximate nearest neighbour search, and hybrid lexical-semantic retrieval.; Experience with query understanding, classification, spell correction, synonyms, or query expansion.; Experience with DSSM, two-tower models, BERT-based ranking, cross-encoders, or similar neural architectures.; Experience with large-scale data and ML platforms such as Airflow, MLflow; Conditions; We know that great talent deserves great conditions, so here's what you can expect when joining us:; EU-based employment contract and a 3-year Cyprus work visa with full support for your relocation and visa processes, including assistance for your family.; Full relocation package: flights to Limassol for you and your family, a company-covered apartment for the first month, and full relocation support to make your move smooth and hassle-free.; Transparent performance reviews twice a year, with bonus opportunities and salary adjustments.; Private medical insurance for you and your family, a corporate mobile plan (unlimited in Cyprus with roaming included), and interest-free support for car purchases.; Provident fund (Cypus): a long-term savings plan co-funded by you and the Company together (available after probation) that grows throughout your time with us in Cyprus.; Mindfulness & well-being support, including psychological assistance with 50% coverage.; 50% coverage of school and kindergarten fees for your children.