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Job Description
Key Responsibilities:
- Use Python, SQL, and R programming to analyze, hypothesize, and solve complex business challenges.
- Employ causal modeling and experimental design to identify growth opportunities.
- Query and extract data using cloud databases, pipeline automation, and scalable analytics.
- Apply statistical modeling and prediction techniques to generate actionable insights.
- Communicate findings to both technical and non-technical audiences, with minimal supervision.
- Data Manipulation: Proficiency in Python and SQL for analyzing large datasets and creating complex queries.
- Statistical Analysis: Advanced knowledge of probability, statistics, exploratory data analysis, hypothesis testing, and experiment design.
- Data Visualization: Expertise in visualization tools like Matplotlib or Seaborn to present complex data insights.
- Model Evaluation: Experience in assessing model performance using metrics such as accuracy, precision, recall, F1 score, and AUC.
- Communication: Strong skills in written, verbal, and visual communication.
- Familiarity with cloud platforms like Snowflake, AWS Sagemaker, AWS Lambda, Airflow, and Jenkins.
- Proficiency in machine learning algorithms (e.g., linear regression, decision trees, random forests, neural networks).
- Experience with feature selection, dimensionality reduction, and model deployment.
- Knowledge of dashboarding tools such as Superset, Looker, or Tableau.
- Preferred experience in credit card, banking, or healthcare domains, along with a strong mathematical background.
Python
SQL
R
Statistical Analysis
Data Visualization
Skills Required for this Role
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