Machine Learning Proficiency: Strong understanding of machine learning algorithms and principles, especially those relevant to anomaly detection, such as supervised and unsupervised learning, clustering, and neural networks.
Soft Skills Needed - This person will be a hands on lead
Prescreening Details - 5 video interview questions and a game
Interview process and when will it start - one round with HM and architect
When do you want this person to start - ASAP
Required Working Hours - Normal working hours
Project person will be supporting - Supply Chain ML Initiative
Team details ie. size, dynamics, locations - Brand new team, will form around this person
Work Location (in office, hybrid, remote) - Remote, EST
Is travel required - No
Requirements
- Strong understanding of machine learning principles, especially anomaly detection techniques
- Expertise in managing, processing, and analyzing large datasets, including data cleaning and feature engineering
- Proficiency in Python programming for machine learning tasks
- Ability to develop and evaluate robust ML models for anomaly detection
- Experience integrating ML models into existing systems, preferably with Azure
- Analytical mindset to identify data patterns indicating anomalies
- Innovative problem-solving skills to enhance anomaly detection
- Attention to detail in model tuning and data interpretation
- Effective communication of ML concepts to non-technical stakeholders
- Collaborative approach to align ML models with business objectives
Typical Duties
- Ensure adherence to architecture standards and roadmaps.
- Implement overall infrastructure/middleware components per project with infrastructure teams, ensuring solutions meet SLA (performance and up-time), DR, and scalability needs.
- Design and successfully implement overall infrastructure/middleware components per project with infrastructure teams, ensuring solutions meet SLA (performance and up-time), DR, and scalability needs.
- Ensure post-production operational processes/deliverables are well designed and implemented before the project moves into the solution support phase.
- Define and create operational procedures, processes, and scripts.
- Follow appropriate change/release management practices.
- Support and maintain infrastructure solutions using necessary tools and technologies, providing off-hours support as required.