KNIME Analytics Platform

Dallas or NJ, 3 days/week in the office is must

1. Data Mining & Analytics:

• Strong understanding of data mining techniques (classification, clustering, regression, anomaly detection, etc.).
• Ability to analyze large datasets, extract insights, and create actionable strategies.

1. KNIME Expertise:

• Hands-on experience with KNIME Analytics Platform for data preprocessing, transformation, and visualization.
• Ability to build and optimize KNIME workflows for data mining tasks.
• Experience with KNIME extensions (e.g., Python, R, Machine Learning, Big Data).

1. Billing Data Analysis (Telecom Use Case):

• Experience analyzing billing and financial datasets to detect patterns, anomalies, and trends.
• Understanding of telecom billing systems and processes (preferably Telecom-specific or similar).
• Ability to identify cost drivers, discrepancies, and revenue leakages using data mining techniques.

1. Data Processing & Integration:

• Experience in handling structured and unstructured data.
• Knowledge of SQL, ETL processes, and data integration with KNIME.
• Understanding of APIs, databases, and cloud platforms (if applicable).

1. Communication & Reporting:

• Ability to translate data findings into business insights.
• Strong experience with data visualization (using KNIME, Power BI, Tableau, etc.).
• Ability to document findings and communicate effectively with stakeholders.

1. Additional Preferred Skills:

• Scripting Knowledge: Python or R (for advanced analytics in KNIME).
• Machine Learning: Basic knowledge of predictive modeling and automation in KNIME.
• Telecom Domain Knowledge: Understanding of billing cycles, usage patterns, and fraud detection in telecom.