Junior Data Scientist
Job Overview
We are seeking a motivated Junior Data Scientist with strong analytical and problem-solving skills to support the development of machine learning and AI-driven solutions. The ideal candidate will have hands-on experience with data analysis, statistical modeling, and foundational GenAI/LLM concepts, along with the ability to work collaboratively in a fast-paced environment.
Mandatory Skills (Core Requirements)
- 2–4 years of experience in Data Science, Machine Learning, or Analytics roles.
- Strong understanding of machine learning techniques including regression, classification, clustering, time series analysis, and recommendation systems.
- Proficiency in Python and related libraries such as pandas, NumPy, scikit-learn, and basic PySpark.
- Strong SQL skills for querying, transformation, and analysis of large datasets.
- Basic hands-on experience with LLMs, prompt engineering, and Retrieval-Augmented Generation (RAG) concepts.
- Knowledge of statistics, hypothesis testing, A/B testing, and model evaluation metrics such as ROC, AUC, precision, and recall.
- Understanding of end-to-end ML lifecycle including model training, deployment, monitoring, and performance tracking.
- Experience working with structured and unstructured datasets in cloud or enterprise environments.
- Strong analytical thinking and problem-solving skills.
- Excellent communication and collaboration abilities.
- Lean Six Sigma Black Belt Certification (preferred/required based on project needs).
Secondary Skills (Nice-to-Have / Enhancing Skills)
- Experience with data visualization tools such as Tableau, Power BI, or Looker.
- Familiarity with cloud and MLOps platforms including AWS, Databricks, MLflow, or feature stores.
- Exposure to customer analytics use cases such as churn prediction, retention analysis, or lead scoring.
- Basic understanding of Responsible AI concepts including SHAP, LIME, explainability, and bias mitigation.
- Ability to work closely with cross-functional teams including Data Engineers, AI Engineers, and business stakeholders.
- Strong willingness to learn new AI/ML technologies and contribute to innovative solutions.
- Experience with version control, CI/CD pipelines, or collaborative development workflows is a plus.