# Data Scientist (Moderation) at Mayflower > Hybrid · Cyprus · Unspecified · Analytics / Data science · open. Source: https://alderhq.app/jobs/recruitee%3Amayflower%3A2731484 (read 2026-11-12). ## Facts (observed) - Company: [Mayflower](https://alderhq.app/companies/mayflower) - Location text: Limassol, Lemesos, Cyprus - Where it can be done from (inferred): Hybrid · Cyprus (evidence: "Location: Limassol, Lemesos, Cyprus") - Posted: 2026-09-02 (71 days ago) - First seen by alder: 2026-11-07 · last verified: 2026-11-07 - Reposted: 0 times · edited: 0 times - Apply on the employer's site: https://mayflower.recruitee.com/o/data-scientist-moderation - Skills listed (inferred): Python, Kafka, SQL, PyTorch, TensorFlow, LLMs ## Pay and sponsorship - Posted pay: not posted - Licensed UK sponsor: registered as "Mayflower" (checked 2026-11-09, [register](https://www.gov.uk/government/publications/register-of-licensed-sponsors-workers)) - Licensed UK sponsor: registered as "The Mayflower" (checked 2026-11-09, [register](https://www.gov.uk/government/publications/register-of-licensed-sponsors-workers)) ## Description (the employer's text) 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 Machine Learning & Modeling • Develop and train machine learning models for prediction, classification. • Build and evaluate regression, classification, clustering, and time-series models. • Design feature engineering pipelines and data preprocessing workflows. • Evaluate model performance, robustness, and production readiness. • Deploy and maintain ML models in collaboration with ml-ops teams. Data Analysis & Exploration • Explore large datasets to identify patterns, trends, and hidden relationships. • Perform statistical analysis and hypothesis testing. • Distillate open-source datasets by proprietary data via LLM agents • Detect anomalies, outliers, and unexpected metric movements. • Translate business or product questions into analytical tasks. Data Pipelines & Infrastructure • Work with data pipelines and streaming data systems. • Process and transform large datasets using Python and SQL. • Work with event streams and messaging systems (Kafka). • Contribute to data quality monitoring and dataset validation. • Work with analytical databases and data warehouses. Model Monitoring & Experimentation • Design experiments and evaluate model performance in real environments. • Implement monitoring for model performance and data drift. • Support A/B testing and experimentation frameworks. • Improve models based on production feedback and metrics. Cross‑Functional Collaboration • Work closely with ML engineers, data engineers, and product teams. • Communicate model results and analytical insights clearly. • Contribute to the development of ML best practices within the team. ### Requirements ### You’ll thrive here if you have • Strong Python programming skills for data science and machine learning. • Experience working in Jupyter / Python notebooks for experimentation and analysis. • Strong experience with pandas and numerical data processing. • Experience with SQL databases and complex analytical queries. • Experience working with ClickHouse or other analytical columnar databases. • Experience working with Kafka or other streaming data platforms. • Experience building and evaluating machine learning models using libraries such as scikit‑learn, XGBoost, LightGBM, or similar. • Understanding of statistics, probability, and experimental design. • Experience working with large datasets and data preprocessing pipelines. Nice to Have • Experience with deep learning frameworks (PyTorch or TensorFlow). • Experience deploying ML models to production environments. • Experience working with Computer Vision models (OpenCV, CNNs, object detection frameworks). • Experience with distributed data processing or large-scale ML systems. • Familiarity with ML monitoring, experiment tracking, and model versioning tools. ### 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. Fully covered sports benefits, and also access to in-house electric scooters and bike rentals, and cycling purchase compensation. Investment in your growth: paid language courses and access to suited-for-you development programs, including conferences, training programs, and coaching to support your professional journey. A culture of recognition: a peer reward program to celebrate your contributions. A fully equipped office in Limassol’s city center, with everything you need for deep work and collaboration. Free catering in the office and an in-house coffee bar with high-quality drinks and a health bar stocked with nutritious snacks. A strong engineering culture: international teams, corporate events, team buildings, and hackathons—because great work happens in great communities. ### Recruitment process HR interview (40 min); Technical interview (1.5 hour); Final interview (60 min). --- Data: alder (https://alderhq.app). Cite https://alderhq.app/jobs/recruitee%3Amayflower%3A2731484 and the date you read it. Observed facts come from the employer's own listing; location reach, level, family and skills are inferences.