As an AI/ML Data Scientist/Engineer Freshers, your role will involve supporting the development and validation of machine learning and statistical models for business use cases. You will assist in building forecasting and predictive models using established techniques and libraries. Additionally, you will contribute to Generative AI use cases, including prompt development, evaluation, and basic experimentation with LLMs. Your responsibilities will also include supporting Retrieval-Augmented Generation (RAG) workflows, such as document ingestion, embeddings, and retrieval.

Key Responsibilities:
- 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
- Build scalable AI/ML models for given use cases, including price elasticity and recommendation systems
- 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

Qualifications Required:
- Bachelor's degree in Computer Science, Statistics, Mathematics, Engineering, or a related quantitative field
- 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

Please note that the job description does not provide any additional details about the company. As an AI/ML Data Scientist/Engineer Freshers, your role will involve supporting the development and validation of machine learning and statistical models for business use cases. You will assist in building forecasting and predictive models using established techniques and libraries. Additionally, you will contribute to Generative AI use cases, including prompt development, evaluation, and basic experimentation with LLMs. Your responsibilities will also include supporting Retrieval-Augmented Generation (RAG) workflows, such as document ingestion, embeddings, and retrieval.

Key Responsibilities:
- 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
- Build scalable AI/ML models for given use cases, including price elasticity and recommendation systems
- 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

Qualifications Required:
- Bachelor's degree in Computer Science, Statistics, Mathematics, Engineering, or a related quantitative field
- 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

Please note that the job description does not provide any additional details about the company.