DI – Data Analytics – ML, GenAI, Python & AWS (CE512SF RM 3883)

Position: DI – Data Analytics – ML, GenAI, Python & AWS (CE512SF RM 3883)

Primary skills: : ML, GenAI, Python and basics of AWS

The Data Analytics Engineer role will focus on requirements and architecting the solutions based on Advanced Data Analytics. This role shall engage with project teams to plan, setup and execute requirements capture and management capabilities.
Master’s degree in Computer Science, Statistics, Math, or Engineering with 5+ years of experience
Required Technical Skills/Education:
-Excellent understanding of data mining , machine learning techniques, Gen AI and algorithms
Knowledge on statistical programming languages, Python, SQL, etc., to process data and gain insights from it
Strong coding experience: Python

• Solid background in database management tools such as SQL
• Broad set of technical skills and expertise in machine learning focused on cutting edge technologies such as IoT, artificial intelligence (AI), and cloud computing.
• Familiar with IoT framework and experience in implementing analytics algorithms in any of the cloud-based platforms – AWS, Azure, GCP
• Fluent English (both written and spoken), solid technical writing, presentation and communication skills.
• Good understanding of control systems

Preferred Technical Skills/Education:

• Strong hands-on experience in an analytics environment and applications.
• Strong hands-on experience in collecting, filtering, organizing, and analyzing large-scale dataset using cloud-based platform.
• Strong hands-on experience in implementing analytics algorithms to cloud-based IoT platforms (Microsoft Azure preferred).
• Strong hands-on experience with the following libraries from Python: Pandas, Numpy, Scipy, Scikit-Learn, TensorFlow, Matplotlib, Seaborn, Plotly, SALib.
• Familiar with vectorized implementation of analytics algorithms.
• Experience with developing end-to-end analytics solution using Python or cloud-based implementation is a plus.

*******************************************************************************************************************************************