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Genpact (NYSE: G) is a global professional services and solutions firm delivering outcomes that shape the future. Our 125,000+ people across 30+ countries are driven by our innate curiosity, entrepreneurial agility, and desire to create lasting value for clients. Powered by our purpose – the relentless pursuit of a world that works better for people – we serve and transform leading enterprises, including the Fortune Global 500, with our deep business and industry knowledge, digital operations services, and expertise in data, technology, and AI 

Inviting applications for the role of Management Trainee – Data Scientist

We are seeking an experienced and skilled Developer-Data Scientist to join our team. In this role, you will be responsible for driving data-driven decision-making and delivering actionable insights through advanced data modelling, statistical analysis, and machine learning techniques. You will leverage your expertise in various domains, including classification, regression, graph transformers, and root cause analysis, to solve complex business problems and drive innovation.
Roles and Responsibilities:
• Design, develop, and implement statistical, machine learning, and deep learning models to solve complex business problems 
• Hands on Python application development
• Fine-tune transformer models for specific tasks and domains 
• Perform ETL (Extract, Transform, Load) activities to prepare data for analysis and modelling. 
• Implement and maintain ML-Ops practices to ensure efficient model deployment and management 
• Analyse large datasets using advanced statistical methods and machine learning techniques 
• Develop and maintain Python-based data processing and analysis scripts 
• Present findings and recommendations to stakeholders in a clear, understandable manner

Qualifications 
Minimum qualifications
• Relevant years of experience in data science and machine learning roles, with a strong understanding of data modelling, statistical analysis, and machine learning techniques. 
• Engineering in relation fields like Computer Science, IT, ML, Data Science
• ML Ops Certification in AWS or Azure
• Strong proficiency in Python programming, including libraries such as NumPy, Pandas, Scikit-learn, PyTorch 
• Extensive experience with deep learning frameworks and techniques 
• Hands-on experience fine-tuning transformer models (e.g., BERT, GPT, T5)
• Knowledge of database systems (e.g., SQL, NoSQL) and experience with data warehousing and data lake architectures. 
• Experience with ETL processes and working with data warehouses 
• Solid understanding of statistical modelling, machine learning algorithms, and their practical applications

Preferred qualifications 

• Familiarity with cloud computing platforms (e.g., AWS, Azure, GCP) and their data services.
• Familiarity with MLOps practices and tools (e.g., MLflow, Kubeflow, or similar)
• Strong understanding of classification, regression, and graph transformer techniques, as well as their applications in various domains.
• Experience in root cause analysis and implementing statistical methods for causal inference and experimental design.
• Excellent problem-solving, analytical, and critical thinking skills.
• Strong communication and collaboration abilities, with the ability to work effectively in cross-functional teams.
• Passion for staying up-to-date with the latest advancements in data science, machine learning, and related technologies.