Data Scientist
Summary
Data Scientist at inDrive in Almaty building production-grade NLP models that automate customer support operations. Owns the full ML lifecycle — research, data/annotation pipelines, deployment, drift monitoring — integrating models with backend services. Core stack: Python (Pandas, NumPy, Scikit-learn), classic ML/deep learning, MLOps.
- Lead the entire machine learning model lifecycle, from initial research and hypothesis testing to production deployment and maintenance
- Translate complex business goals into well defined data science problems and quantifiable metrics
- Design and develop robust, scalable machine learning systems from scratch, including data analysis, annotation, and processing pipelines
- Contribute to the overall system architecture and integrate ML models with existing backend services and infrastructure
- Monitor and maintain deployed models, proactively identifying and addressing issues like concept drift to ensure consistent performance
- Support the development and growth of other team members through mentorship and participation in onboarding programs
- Drive continuous improvement by automating repetitive tasks and proposing innovative solutions that lead to significant business impact
- Communicate complex technical concepts and findings clearly and concisely to both technical and non technical stakeholders
- 5 years of professional experience in a data science or machine learning role with deep focus on NLP.
- Previous software engineering experience is preferrable.
- An academic background in a quantitative field such as Computer Science, Mathematics, or a related discipline will be a plus
- Expert level proficiency in Python and its core data science libraries (e.g., Pandas, NumPy, Scikit learn).
- Deep expertise in classic machine learning and deep learning techniques, with a strong understanding of advanced mathematics relevant to these fields.
- Experience with ML system design and MLOps practices for building, testing, deploying, and monitoring models in a production environment.
- Proven experience with event systems, deployment environments, and maintaining production services.
- Familiarity with technologies for streaming, batch, and async data processing.
- Strong understanding of software system design principles and the ability to contribute to architectural discussions.
- Experience in experimental design to validate hypotheses and measure the effectiveness of solutions.
- A solid grasp of security, risk, and control concepts in a production environment.
- Help us challenge injustice by creating fair choices for millions of people across 1100+ cities in 48 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.