Senior Data Scientist – Geo Search

This is a fully remote position, open to applicants in Kazakhstan.

📋 Description

• Create and develop deep learning systems for search ranking, session-based recommendations, and multi-objective personalization.

• Ensure that ranking incorporates geographic context while managing the recommendation and ranking of pickup locations.

• Convert business objectives into machine learning goals along with non-functional requirements.

• Lead assessments from offline metrics through the design of online A/B tests, demonstrating enhanced engagement prior to implementing changes.

• Collaborate with backend engineers to transition models from prototype to production, focusing on model serving and latency optimization.

• Work closely with the product manager and operations team to transform behavior analysis into tangible features and requirements.

• Oversee the production machine learning lifecycle, encompassing model serving, drift monitoring, and retraining pipelines.

• Engage in tasks related to place search and autocomplete, geocoding, ranking and personalization, location detection and pickup selection, external-provider integrations, as well as Android/iOS search screens.

• Assess impact using offline evaluation metrics and online A/B tests.

⛳️ Requirements

• A minimum of 5 years of experience in machine learning engineering, with at least 3 years focused on building and deploying deep learning models in a production environment.

• Hands-on experience with search, NLP, ranking, recommendation, or relevance systems.

• Advanced proficiency in Python and essential data science libraries, as well as SQL, including tools such as PySpark, Pandas, NumPy, Scikit-learn, and PyTorch.

• Capability to design an ML system from the ground up, covering data analysis, annotation, processing, and production model serving.

• Experience in translating business objectives into ML challenges with proxy metrics and non-functional requirements.

• Proven background in designing or significantly contributing to A/B tests and statistical evaluations.

• Familiarity with MLOps tools and practices for managing the machine learning model lifecycle.

• Experience in deploying models to production on ML serving infrastructure and optimizing for latency.

• Understanding of concept drift and methods for detecting and managing it.

• Strong ability to influence colleagues and partner teams, clearly communicating complex results.

• A degree in Computer Science, Mathematics, or a related quantitative field is advantageous but not mandatory.

• Additional strengths include experience in fine-tuning and deploying large or small language models, relevance in geocoding or autocomplete, mapping/location/geospatial products, developing market products, and certifications in BigQuery or Databricks.

🏝️ Benefits

• Enhance your professional skills through access to mentoring, career consulting, and learning programs.

• Collaborate with global teams and gain international exposure via our Global Talent Exchange Program.

• Participate in company-wide challenges, awards, sports activities, and employee-led social impact and volunteering initiatives.

• Improve your language proficiency with co-financed courses and internal speaking clubs.

• Contribute to combating injustice by creating equitable choices for millions across 1100+ cities in 48 countries.

• Work with individuals who take initiative, communicate openly, and strive for personal growth.

• Final benefits may vary based on location.