Description
Key Skills: Python, SQL, Machine Learning, Data Visualization, Statistical Analysis, Pandas, NumPy, Scikit-learn, Tableau, Power BI
Good to Have Skills: Version control systems like Git, cloud platforms such as AWS, Azure, or GCP, big data technologies including Spark and Hadoop, experience with data science bootcamps or Kaggle competitions, semantic search techniques, RAG framework for Gen AI solutions, Agentic solutions using Langchain or Google Agent space frameworks.
Roles & Responsibilities:
- Assist in collecting, cleaning, and preprocessing large datasets to ensure data quality and integrity.
- Conduct basic exploratory data analysis to identify trends, patterns, and insights from various datasets.
- Support the creation and selection of features for machine learning models under senior guidance.
- Help in building, training, and evaluating basic machine learning models with proper supervision.
- Maintain clear and concise documentation of data processes, models, and analytical findings for team reference.
- Work closely with senior data scientists, engineers, and business stakeholders to achieve project objectives.
- Actively participate in training programs, workshops, and self-study to enhance data science skills continuously.
- Assist in preparing reports and visualizations to communicate findings effectively to technical and non-technical audiences.
- Develop search techniques especially semantic search solutions for improved data discovery and analysis.
- Develop solutions using RAG framework for building Gen AI solutions in various business applications.
- Develop Agentic solutions using frameworks like Langchain or Google Agent space for automated processes.
Education: Bachelor's or Master's degree in a quantitative field such as Computer Science, Statistics, Mathematics, Economics, Engineering, or a related discipline