Analyst - Data Scientist Machine Learning

Role Overview

Job Overview and Responsibilities

• Partner with business teams to identify improvement opportunities, gather and analyze data, develop solutions, and drive innovation.
• Apply statistics, machine learning, programming, and data modeling to identify patterns and deliver high-impact models.
• Communicate insights through clear, professional presentations to teams, leaders, managers, and stakeholders.
• Develop end-to-end project pipelines to deploy scalable solutions on company platforms.
• Execute business solutions using data analysis, machine learning, and optimization tools.
• Mentor junior resources on data science skills.
• Research emerging machine learning models and share knowledge across the team.

Minimum Qualifications

• Bachelor's degree in engineering, technology, computer science, statistics, operations research, applied mathematics, or economics.
• At least 2 years of full-time relevant analytics or data science experience.
• Strong foundation in machine learning, statistics, and applied mathematics with hands-on business problem-solving experience.
• Strong Python and SQL proficiency with large and complex datasets.
• Experience across data preparation, model development, evaluation, and production deployment in the ML lifecycle.
• Hands-on experience with classification, regression, ensemble methods, gradient boosting, and clustering.
• Hands-on Generative AI and foundation-model experience including prompt engineering, embeddings, vector search, RAG, and AI agents.
• Ability to translate business problems into AI/ML solutions and define success metrics.
• Strong analytical, problem-solving, communication, independent work, and cross-functional collaboration abilities.

Preferred Qualifications

• Master's degree or MTech in a relevant analytical, engineering, technology, computer science, statistics, operations research, mathematics, or economics discipline.
• Hands-on deep learning and neural network experience with PyTorch or TensorFlow.
• Experience in Computer Vision, Generative AI, LLMs, or Natural Language Processing.
• Experience building production-grade AI/ML systems including serving, inference, monitoring, optimization, and lifecycle management.
• Experience with AWS ML platforms including SageMaker, S3, Redshift, Athena, and data lake architectures.
• Experience with MLOps, CI/CD, model versioning, experiment tracking, automated pipelines, monitoring, distributed processing, or large-scale ML.

Employment Terms

• The position is offered on local terms and conditions. Expatriate assignments and employment visa sponsorship are not available.