Data Scientist

Job description

Key Responsibilities

• Analyze large datasets to identify trends, patterns, and actionable business insights.
• Build, test, and evaluate machine learning and statistical models for classification, regression, forecasting, segmentation, and predictive analytics.
• Perform data cleaning, feature engineering, exploratory data analysis (EDA), and model validation.
• Develop solutions using Python, Pandas, NumPy, Scikit-learn, and related ML libraries.
• Write efficient SQL queries for data extraction, transformation, and analysis.
• Evaluate models using appropriate metrics such as precision, recall, F1-score, ROC-AUC, RMSE, and MAE.
• Create dashboards, reports, or visualizations using tools such as Power BI, Tableau, Matplotlib, or Seaborn.
• Work closely with data engineers, senior data scientists, and business stakeholders to take analytical solutions from experimentation to implementation.
• Document methodologies, experiments, model results, and key findings.
• Assist with GenAI/LLM use cases, including prompt engineering, embeddings, and RAG-based solutions, where applicable.

Required Skills

• 2-7 years of experience in Data Science, Machine Learning, or Advanced Analytics.
• Strong programming skills in Python.
• Good knowledge of SQL and relational databases.
• Understanding of supervised and unsupervised machine learning techniques.
• Strong foundation in statistics, probability, hypothesis testing, and data analysis.
• Hands-on experience with Pandas, NumPy, Scikit-learn and data visualization libraries.
• Understanding of model evaluation, feature selection, cross-validation, and overfitting.
• Good analytical and problem-solving skills.
• Strong communication skills with the ability to explain analytical findings clearly.