The Data Scientist will leverage critical thinking and data analysis skills to develop Machine Learning models for detecting financial crime risks and synthesizing data requirements.
This is a remote position.
Responsibilities:
- The Data Intelligence & Analytics Analyst must demonstrate critical thinking, analytical and problem-solving abilities, hands-on intelligence or data analysis skills, network analysis acumen, and intellectual curiosity is essential for data science tasks.
- The candidate must be able to apply these abilities to detect non-obvious risks or develop, test, and champion ideas to increase detection.
- The candidate should understand data science methods, and visualization techniques to leverage internal and external data to identify and develop ways to systemically detect financial crime risk.
- Research & develop Machine Learning models for security problems, in the areas of Networking, Application & Data.
- Suggest, collect and synthesize requirements and create effective features.
- Apply research methodologies to identify the Machine Learning models for the problem at hand.
Requirements
Preferred Qualifications:
- Domain expertise in Networking ( TCP/IP, HTTP) , Web Application Security (Bot detection ) is preferred
- Experience working with relational and NoSQL/Graph databases
- Unsupervised & Deep Learning Experience
- Familiar with Big Data frameworks (Hadoop or Spark) and cloud infrastructures
- Experience in applying Machine Learning techniques
- Ability and willingness to multi-task and learn new technologies quickly
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What you need to know about the Delhi Tech Scene
Delhi, India's capital city, is a place where tradition and progress co-exist. While Old Delhi is known for its rich history and bustling markets, New Delhi is defined by its modern architecture. It's clear the region places a strong emphasis on preserving its cultural heritage while embracing technological advancements, particularly in artificial intelligence, which plays a central role in shaping the city's tech landscape, fueled by investments in research and development.
