Data Analyst Engineer - Classification And Profiling (India - Remote)

Company Overview

AtOrdr, we are singularly focused on helping our customers find order where once there was chaos. We make the incredibly complex problem of Connected Device Security incredibly simple, and we take great pride in the fact that we continually strive for approachable innovation in everything we do. In today's hyper-connected enterprise, where everything from access badge scanners to digital signage to inventory control systems to multi-million-dollar healthcare and manufacturing systems, traditional network regulation and security models simply cannot scale.Ordrsolves this problem with our AI-powered Connected Device Security platform, providing enterprises with complete visibility and security over every class of network-connected devices and systems.

Join our world-class Ordr team!Help us deliver our customers a world-classConnected Device Securityplatform while having fun.

Our small and startup company culture empowers our employees to work on exciting, state-of-the-art technology. It allows them to be a part of an excellent, fast-growing company. OurAI-powered Connected Device Security platformhas a rich GUI interface that visualizes network entities, security incidences, and vulnerabilities.

Job Title: Data Analyst Engineer - Classification and Profiling

Location: Bengaluru, KA (India)

Responsibilities:

Data Profiling:

• Develop and maintain classification, device profiling with data analytics, data cleanup, and feature engineering.
• Utilize AI/ML techniques to enhance the profile library. Collaborate with internal and external resources to add to the knowledge base and profile library.
• Utilize AI/ML techniques to enhance the profile library. Collaborate with internal and external resources to add to the knowledge base and profile library.
• Work with Ordr data lake with a knowledge base of millions of devices to leverage it for supervised learning.
• Develop rule-based engines for attribute mapping.

Data Collection and Feature Engineering

• Gather additional data from customers to assist in classification. Crawl the internet for information on manufacturers, devices, and their make/model/modality.
• Gather additional data from customers to assist in classification. Crawl the internet for information on manufacturers, devices, and their make/model/modality.
• Collect data through protocol interactions and queries for classification purposes.
• Use Deep Packet Inspection to identify valuable data for Classification and Implement network packet parsers for data extraction.
• Build and enhance tools for device Classification and analysis.
• Design and engineer features from raw data to improve model performance and interpretability.

Data Analytics

• Identify and rectify anomalies in large datasets using domain knowledge and data profiling techniques.
• Collaborate with cross-functional teams to understand data requirements and ensure data quality.
• Work with software engineers to deploy machine learning models into production environments.
• Ensure seamless integration of models with existing data infrastructure and applications.
• Monitor model performance in real time and implement necessary updates or improvements.
• Ongoing operational support to the customer

Requirements:

• Bachelor's or Master's degree in Computer Science, Mathematics, or a related field.
• Proven experience in deep packet inspection and data processing in a large-scale data environment.
• Proficiency in machine learning algorithms.
• Hands-on experience with data manipulation libraries/tools like Pandas, NumPy, and SQL.
• Proficiency in programming languages such as Python for data analysis and modeling.
• Experience with data visualization tools for exploratory data analysis and model interpretation.
• Experience with cloud platforms (e.g., AWS, Azure, Google Cloud) and associated data services.

Personal Attributes:

• Excellent problem-solving skills and the ability to work independently and with a team of consultants.
• Strong communication skills with the ability to effectively convey technical concepts to non-technical stakeholders.
• Comfortable working effectively with cross-functional and remote team members.
• Self-motivated, Self-starter, Self-organized
• Good documentation skills.
• Recognizes the importance of internal and external deadlines.
• Strong logical and creative problem-solving skills, good oral and written communication skills, and excellent analytical skills.
• Must be able to succeed with minimal resources and minimal supervision.