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
Bachelors 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