Data Manipulation: Proficiency in using Python libraries like Pandas, NumPy, and SciPy to efficiently manipulate and analyze large datasets. Strong experience in extracting and reporting data using complex queries.
Statistical Analysis: Proficiency with statistical concepts and techniques, including exploratory data analysis, hypothesis testing, confidence intervals, and experiment design. Proficiency in using statistical methods to derive meaningful conclusions from data.
Data Visualization: Proficiency in using visualization libraries like Matplotlib or Seaborn to create clear, concise, and intuitive visualizations that communicate complex data insights to stakeholders.
Model Evaluation and Validation: Proficiency in assessing model performance using metrics such as accuracy, precision, recall, F1 score, and area under the curve (AUC). Proficiency in techniques like cross-validation, train-test splits, and hyperparameter tuning to ensure robust model performance.
Communication: Strong written, verbal, and visual communication skills.

Desired Skills

Cloud platforms: Familiarity with cloud platforms for data analysis and orchestration like , AWS Lambda, Airflow, Jenkins, Postman
Machine Learning: Proficiency with fundamental machine learning algorithms such as linear regression, logistic regression, decision trees, random forests, and neural networks. Ability to use ML and statistical modeling to solve business problems.
Feature Selection and Dimensionality Reduction: Familiarity with techniques like feature selection, feature engineering, regularization, and dimensionality reduction (e.g., PCA) to improve model efficiency, reduce overfitting, and enhance interpretability.
Model Deployment: Experience in deploying machine learning models in production environments, utilizing frameworks like Flask or Django. Understanding of model serving, API development, and cloud deployment to enable real-time predictions.
Dashboarding: Familiarity with BI and dashboarding software such as Superset, Looker and Tableau.
Candidates with experience in the credit card, banking, or healthcare domains and/or strong mathematical and statistical backgrounds will be preferred.

Internal Mobility