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Data Analyst Engineer- Series C
4 months ago
We’re looking for a Data Analyst Engineer to join our world class team in Bangalore within 1 Month notice.
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. Our AI-powered IoT security platform has a rich GUI interface that visualizes network entities, security incidences, and vulnerabilities.
Experience: 5-8 Years
Responsibilities:
Data Profiling:
- Develop and maintain classification, device profiling with data analytics and data cleanup and feature engineering.
- Utilize AI/ML techniques to enhance the profile library. Collaborate with a consulting team to build the profile library.
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. Collect data through probes for classification purposes.
- Perform feature engineering from sparse matrix data.
- Use Deep Packet Inspection to identify useful 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.
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 such as Pandas, NumPy, and SQL.
- Proficiency in programming languages such as Python for data analysis and modelling.
- Experience with data visualization tools for exploratory data analysis and model interpretation.
- Excellent problem-solving skills and the ability to work independently as well as with a team of consultants.
- Strong communication skills with the ability to effectively convey technical concepts to non-technical stakeholders.
- Experience with cloud platforms (e.g., AWS, Azure, Google Cloud) and associated data services.
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