Senior Data Scientist (Geo Search)
Geo Search runs the search that tens of millions of customers use to say where they are going, across many countries where the commercial maps everyone else leans on are often wrong, incomplete, or simply missing. We are building our own s…
indrive · На сервисе с: 03.10.26 16:12
About the role
We are looking for a Senior Data Scientist to own ranking, relevance and recommendation for geo search: the models that decide which places a customer sees, in what order, and how that changes with context.
This is a modeling role with production responsibility, and it is close to a founding one. You will define how relevance is measured here, build the training data from scratch, and own the models that follow. The interesting constraint is that suggestions must return within tens of milliseconds of each keystroke, in cities where map data is thin and people type in mixed scripts, so model choice is an evidence-based trade-off you will own rather than a preference: gradient-boosted ranking on behavioral data today, transformers and large language models where they earn their place in query understanding and cross-script matching, and neural reranking if the failure analysis justifies it. Ground truth comes from what drivers, couriers and customers actually do, and from completed rides, so a large part of the craft is turning messy behavioral logs into labels you can trust. You will measure your impact through offline evaluation and online A/B tests, and changes reach millions of customers in weeks.
Responsibilities
- Own ranking, relevance and recommendation for geo search end to end, from training data through to models serving in production
- Build the label pipeline that turns search sessions and completed rides into trustworthy training data, including correction for position bias and other presentation effects
- Train and own the models that order results, and the confidence model that decides per query whether we serve our own answer or fall back to an external provider
- Build query understanding for our markets, including cross-script matching, using large language models to label offline and distilling into models fast enough for the keystroke path
- Own evaluation end to end: the offline replay harness that scores recorded sessions against real rides, the error analysis that turns failures into work for the right team, and the online experiments that prove impact
- Keep models healthy after launch as data and cities shift
Qualifications
- 5 or more years building models that shipped and improved a production metric
- Direct experience with ranking, search relevance, or recommendation systems, including how they are evaluated
- Expert Python and SQL, fluency with gradient boosting, and working knowledge of transformers
- Experience taking a model to production and owning it afterwards
- The ability to work across teams, since search quality work generates data and engineering tasks that others own
Preferred qualifications - Depth in geocoding, autocomplete, or place search
- Learning to rank in practice: pairwise and listwise objectives, MRR, NDCG, Hit@k, and their failure modes
- Relevance tuning on OpenSearch or Elasticsearch, including analyzers
- Multilingual or cross-script search, for example Arabic and Arabizi or Urdu and Roman Urdu
- Distilling language models under a latency budget, and experience in mapping or geospatial products in developing markets
Benefits
- Help us challenge injustice by creating fair choices for millions of people across 47 countries.
- Develop your professional skills with access to mentoring, career consulting, and learning programs.
- Collaborate with teams around the world and gain international experience through our Global Talent Exchange Program.
- Engage in company-wide challenges, awards, sports activities, employee-led social impact and volunteering projects.
- Work alongside people who take initiative, speak openly, and challenge themselves to grow.
- Improve your language skills through co-financed courses and internal speaking clubs.
Похожие вакансии Data Science & ML
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.
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.
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 (45 min).
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.
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).
About the role
Responsibilities
- Design and improve dynamic pricing policies, including elasticity and supply/demand response modeling
- Frame pricing as a decision system under uncertainty and delayed feedback
- Develop, test, and deploy real-time pricing algorithms
- Design and analyze A/B experiments to evaluate pricing impact
- Productionize models in collaboration with engineering, ensuring scalability and robustness
- Monitor system performance, including stability, feedback effects, and long-term behavior
- Contribute to methodological choices (e.g., optimization, control, RL-inspired approaches)
Qualifications
- 3+ years of experience in Data Science, Applied Research, or algorithmic product optimization, preferably in marketplaces or pricing systems
- Strong background in statistics, optimization, and causal inference
- Proven ability to move from problem formulation to production-grade solutions
- Proficiency in Python, SQL, and experience with production ML systems
Nice to Have
- Experience with economic modeling (elasticity, auctions, policy design)
- Familiarity with control systems, RL, or online optimization
- Experience working with real-time, high-load systems
Benefits
- Help us challenge injustice by creating fair choices for millions of people across in 47 countries
- Develop your professional skills with access to mentoring, career consulting, and learning programs
- Collaborate with teams around the world and gain international experience through our Global Talent Exchange Program
- Engage in company-wide challenges, awards, sports activities, employee-led social impact and volunteering projects
- Work alongside people who take initiative, speak openly, and challenge themselves to grow
- Improve your language skills through co-financed courses and internal speaking clubs
- Annual salary from EUR 80 200 gross
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