Operations Analyst (Machine learning Data Management)

Key Skills

Apache Hadoop, C Programming, C++, Data science techniques, Java Programming, Machine learning techniques, MapReduce, Python Programming, PyTorch, R Programming, Scala Programming, SQL, TensorFlow

Job Description

Responsibilities

As a Data Operations Analyst, you will design and establish efficient processes that sit at the intersection of data management/engineering and machine learning. Your responsibilities touch on all aspects of data analysis and ML data management which include

• Maintain and index datasets.
• Visualize metrics and catalog corner cases.
• Acquire and manage ML train/val datasets.
• Acquire and manage ground-truth labels.
• Create instructions and coordinate with ground-truth annotators.
• Coordinate with ML research, software, and QA teams.
• Understand the driving rules of various countries across the globe.

Requirements

• B.E / B. Tech, M.E / M. Tech with 5+ years of relevant work experience.
• Excellent written and verbal communication skills.
• Familiarity with ML concepts, such as supervised learning, accuracy, precision, etc.
• Experience with databases (SQL/NoSQL) and AWS environment.
• Ability to write basic scripts – Python (required).
• Excellent problem-solving and project management skills.
• Detail-oriented, analytical, and creative thinker with a passion for quality.
• Flexible and can-do approach. Ability to adjust to changing priorities.
• Passionate about becoming an expert in the area of AI/ML.

Desired Skills

• Experience with leading/guiding a small team is a plus.
• Familiarity with ML concepts, such as active learning, generalization, etc. is a plus.
• Completion of AI/ML courses (e.g., https://www.coursera.org/specializations/deep-learning).
• Familiarity with data visualization software (e.g., Tableau, Plotly-Dash) is a plus.
• Experience computer Vision and image/video processing is a plus.