Data Scientist - Supply Chain Solutions-Remote

Reposted 12 Days Ago
Be an Early Applicant
5 Locations
Remote
Senior level
Artificial Intelligence • Information Technology
The Role
Seeking a Data Scientist to develop ML solutions for supply chain management, focusing on inventory. Requires collaboration and expertise in Python, Databricks, Snowflake, and AWS.
Summary Generated by Built In

At Xenon7, we work with leading enterprises and innovative startups on exciting, cutting-edge projects that leverage the latest technologies across various domains of IT including Data, Web, Infrastructure, AI, and many others. Our expertise in IT solutions development and on-demand resources allows us to partner with clients on transformative initiatives, driving innovation and business growth. Whether it's empowering global organizations or collaborating with trailblazing startups, we are committed to delivering advanced, impactful solutions that meet today’s most complex challenges.


Requirements

Role Overview

We are seeking a highly skilled Data scientisit with strong expertise in Python, Databricks, Snowflake, and AWS to design, develop, and deploy advanced ML solutions. The ideal candidate will possess deep functional knowledge of supply chain management—particularly inventory management—and demonstrate hands-on experience with key machine learning algorithms, including time series forecasting, regression models, and neural networks. This role requires end-to-end ownership, from business requirement gathering to solution delivery, along with exceptional communication and stakeholder management skills.

Key Responsibilities

  • Collaborate with business stakeholders to gather and analyze requirements, ensuring alignment with project objectives.
  • Architect and implement ML models for supply chain and inventory management use cases.
  • Work with Python, Databricks, and Snowflake for data preparation, modeling, and pipeline development.
  • Leverage AWS services to build, deploy, and scale ML solutions in production environments.
  • Apply advanced algorithms including time series forecasting, regression, LSTM, neural networks, and classification models.
  • Drive discussions, present solutions, and take full ownership of the end-to-end ML delivery process.
  • Continuously monitor, evaluate, and optimize model performance.

Required Technical Skills

  • Programming & Data Platforms: Python, Databricks, Snowflake
  • Cloud Services: AWS (ML and deployment-relevant services)
  • Machine Learning Expertise: Time series forecasting, regression, LSTM, neural networks, classification models

Functional Expertise

  • Strong understanding of Supply Chain Management, with a focus on inventory management processes and challenges.

Professional Skills

  • Proven ability to gather business requirements and translate them into technical solutions.
  • Strong problem-solving mindset with a proactive and ownership-driven approach.
  • Excellent communication skills (verbal and written) for engaging with technical and non-technical stakeholders.

Qualifications

  • Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related field.
  • 5+ years of relevant experience in ML engineering, data science, or AI solution delivery.
  • Prior experience in supply chain ML applications is highly desirable.

Skills Required

  • 5+ years of relevant experience in ML engineering, data science, or AI solution delivery
  • Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or a related field
  • Strong understanding of Supply Chain Management
  • Hands-on experience with time series forecasting, regression, LSTM, neural networks, and classification models
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The Company
11 Employees

What We Do

Xenon7 delivers specialized AI operations, AI products and services. Our innovation practice helps you separate initiatives warranting business investment from hype. We operate free from the bloat, weight and pyramidal structure of legacy consulting firms. Xenon7 enables our clients to make better human and technology decisions, and ethically achieve more with less

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