Senior Data Scientist

inDrive; Egypt (PA); On-site; USD 18,000 - 28,000; Full time

Job summary

inDrive in Egypt seeks a Senior Data Scientist to architect, build and deploy NLP models that automate customer support operations. You will select the right approaches and ensure scalable solutions across production environments.

The role leads the full ML lifecycle, translates business goals into measurable data science problems, and collaborates with backend teams to integrate models with existing services.

Qualifications

• 5+ years in data science or ML with NLP focus.
• Strong Python and data science library skills.
• Experience in production ML, ML Ops, and scalable systems.

Responsibilities

• Lead model lifecycle from research to production deployment.
• Translate business goals into data science problems with measurable metrics.
• Design scalable ML systems including data processing pipelines.
• Integrate ML models with backend services and infrastructure.
• Monitor models in production and address issues like drift.
• Mentor teammates and contribute to onboarding.
• Drive automation and innovative solutions with business impact.
• Communicate complex results to technical and non-technical stakeholders.

Skills

NLP

Python

ML systems

MLOps

Production deployment

Data pipelines

Pandas

NumPy

Scikit-Learn

Software engineering

Education

Master's or PhD in CS/Math or related

Tools

Python

Pandas

NumPy

Scikit-learn

MLflow

TensorFlow/PyTorch

Job description

Senior Data Scientist

Department: AI Cluster

Employment Type: Full Time

Location: Egypt

Description

The AI Solution Delivery team is expanding its capabilities in NLP to build production-grade AI products. We are looking for a Senior Data Scientist to architect, build and deploy complex models for automating customer support operations. You will be responsible for selecting the right technical approaches and ensuring the scalability of our solutions. A proven track record in applying advanced NLP techniques to real-world problems is required.

Key Responsibilities

• 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

Skills, Knowledge and Expertise

• 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.

Conditions & Benefits

• 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.

Final benefits may vary depending on the location.