Benefits and conditions

• Fully remote job.
• Flexible schedules to have a work-life balance.
• All required equipment will be provided.
• Dynamic and interesting work with lots of growth opportunities.

Requirements

• Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or a related field.
• Proven experience as a Data Architect, Machine Learning Engineer, or in a similar role, with a strong portfolio of successful projects.
  
• Expertise in machine learning algorithms, data modeling, and statistical analysis.
  
• Extensive experience in Data Architecture and Machine Learning, with a demonstrable focus on AI/ML operations and implementation of enterprise-wide data frameworks.
  
• Proficient in using Snowflake and various AWS services, such as Sagemaker, for data warehousing and machine learning projects.
  
• Strong programming skills in Python, SQL, and other relevant languages/frameworks.
  
• Excellent analytical, problem-solving, and project management skills.
  
• Ability to work collaboratively in a team environment and communicate complex technical concepts to non-technical stakeholders.
• Experience with implementing automated testing frameworks within the data ecosystem is a big plus.
• Fluent in English, with excellent verbal and written communication skills.

Soft skills

• Strong communication skills
• High-level english communication is needed. 
• Team-work player, proactive and great attitude.

Responsibilities

• The successful candidate will play a pivotal role in identifying cross-sell/up-sell opportunities, addressing lost demand, and enhancing demand forecasting. Utilizing disparate marketplace data and integrating various data sources will be a key responsibility, aiming to extract valuable insights and drive strategic decisions.
  
• Architect and enforce scalable AI/ML operational frameworks to support our machine learning and analytics initiatives, ensuring scalability, efficiency, and security across the enterprise.
  
• Build and deploy sophisticated machine learning models to unlock business opportunities and enhance predictive analytics capabilities.
  
• Design and implement robust data architectures to support machine learning and analytics initiatives, ensuring scalability, efficiency, and security.
  
• Develop and deploy advanced machine learning models to identify cross-sell/up-sell opportunities, forecast demand, and optimize inventory management.
  
• Analyze and integrate disparate marketplace data, identifying patterns and insights that can drive business strategy and operational improvements.
  
• Collaborate with cross-functional teams to understand business needs, gather requirements, and translate them into technical specifications.
  
• Leverage Snowflake for data warehousing solutions, ensuring optimal performance, data integrity, and compliance with data governance standards.
  
• Explore and implement AWS services, including Sagemaker, to enhance machine learning capabilities and automate data processing workflows.
  
• Continuously monitor, evaluate, and improve the performance of data systems and machine learning models, incorporating feedback and emerging technologies.
  
• Provide technical leadership and mentorship to junior team members, fostering a culture of innovation and continuous learning.