AI/ML Data Scientist/Engineer Freshers
Responsibilities
€¢ Support development and validation of machine learning and statistical models for business use cases
€¢ Assist in building forecasting and predictive models using established techniques and libraries
€¢ Contribute to Generative AI use cases including prompt development, evaluation, and basic experimentation with LLMs
€¢ Support Retrieval-Augmented Generation (RAG) workflows including document ingestion, embeddings, and retrieval
€¢ Perform data preparation, feature engineering, and exploratory data analysis
€¢ Work with structured and unstructured data from enterprise sources and AI platforms
€¢ Collaborate with software engineers to integrate models into applications and pipelines
€¢ Help document models, assumptions, results, and data pipelines
€¢ Monitor model performance and assist with troubleshooting and improvements
€¢ Participate in agile ceremonies including sprint planning, stand-ups, and retrospectives
€¢ Build scalable AI/ML models for given use cases, including price elasticity and recommendation systems, ensuring applicability/reusability across multiple business units.
€¢ Leverage tools such as Databricks and AWS SageMaker to manage data, build models, and deploy solutions.
€¢ Collaborate with stakeholders, understanding their needs and translating them into AI/ML solutions.
€¢ Continually monitor and evaluate the effectiveness of AI/ML models and forecasting techniques, making necessary adjustments to optimize performance.
€¢ Stay abreast of the latest AI/ML trends and technologies, identifying opportunities for innovation and improvement
Education & Experience
Bachelor€™s degree in Computer Science, Statistics, Mathematics, Engineering, or a related quantitative field.
Required Skills
€¢ Proficiency in Python and familiarity with data science libraries (pandas, NumPy, scikit-learn)
€¢ Basic understanding of machine learning algorithms and statistical modeling techniques
€¢ Experience working with SQL and relational or NoSQL databases
€¢ Exposure to cloud or data platforms such as Databricks or AWS
€¢ Familiarity with version control tools such as Git
€¢ Ability to clearly communicate data insights and document work
€¢ Experience working in agile or Scrum-based teams