Junior Data Scientist – Delivery Lead Data & AI

Job Overview

We are looking for a motivated Junior Data Scientist to join our Data & AI Delivery team. In this role, you will collaborate with senior data scientists and delivery leads to design, develop, and deploy AI/ML solutions that solve real-world business problems. This is an excellent opportunity for early-career professionals passionate about data science and eager to grow into future technical leaders in AI and analytics.

Key Responsibilities

• Assist in building end-to-end data science workflows including data ingestion, preprocessing, modeling, and deployment.
• Support integration and deployment of ML models into business applications via APIs.
• Develop, test, and validate machine learning models under guidance from senior team members.
• Perform exploratory data analysis (EDA), feature engineering, and data cleaning using Python and SQL.
• Work with big data processing frameworks such as Spark or Hadoop in real-world projects.
• Gain exposure to Generative AI (e.g., GPT, Hugging Face Transformers) and contribute to fine-tuning and experimentation.
• Participate in pilots involving Generative AI for text generation, conversational AI, and content automation.
• Assist in deploying ML models using MLOps tools and pipelines (MLflow, TFX, Kubeflow).
• Monitor model performance, track metrics, and troubleshoot production issues.
• Support the orchestration and management of AI workloads using Kubernetes.
• Collaborate with data scientists, engineers, and business stakeholders to understand requirements and deliver insights.
• Document workflows, experiments, and project outcomes for knowledge sharing and reusability.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, or a related field.
• Strong programming foundation in Python (R or Scala is a plus).
• Good understanding of machine learning algorithms and libraries such as scikit-learn, TensorFlow, and PyTorch.
• Hands-on experience with SQL and data wrangling.
• Familiarity with APIs (REST/GraphQL) for ML model integration.
• Basic understanding or exposure to Kubernetes and Docker for deployment.
• Experience or exposure to cloud platforms like AWS, Azure, or GCP through projects or internships.
• Curiosity and eagerness to learn advanced areas such as MLOps, Big Data, and Generative AI.
• Strong analytical and problem-solving skills with a collaborative mindset.
• Experience in building GenAI applications, internships, or Kaggle/competition projects in ML/AI is a plus.