At Altana, we are bringing about a better globalization by facilitating visibility, decision support, and collaboration across global business networks.  We have built a fundamental understanding of how the world’s economy works by mapping how physical goods transit and transform as they flow through the world’s business networks.  These insights are based on our extensive proprietary data network across the world’s largest supply chain data corpuses, and using modern ML and data science to infer, analyze, and make sense of the physical world.  We are pushing the envelope to build a foundational AI for the world’s physical economy.

We are looking for a talented machine learning and data science leader to guide initiatives across the company.  As VP of Machine Learning and Data Science, you’ll be responsible for the approaches, culture, recruiting, leadership, and work product of several teams that are critical to Altana’s success.  You’ll oversee the machine learning and data science components of core product features such as entity resolution for our graph construction process, information retrieval for search, recommender systems for supplier identification and vetting, customs classification and prediction, graph analyses, and reinforcement learning across our user base that includes the world’s largest customs authorities, logistics providers, enterprises, and supply chain software application providers.  In this role you’ll report to the Chief Technical Officer and help create the culture and environment by which we use state of the art AI + ML.  

Responsibilities

• Manage a cross-functional team of talented Data Scientists, Analysts, and Machine Learning Engineers embedded in several product teams delivering core product features to users.
• Direct client facing teams to ensure their data science customizations for clients are in line with long term product and ML vision (e.g. collecting right data to feedback into RLHF workflows, customizing appropriately for client specific needs, etc.).
• Define Altana's data and machine learning technology standards, and oversee the training, mentorship, and performance of a world-class technology team.
• Collaborate and build strong relationships with Product, Engineering, and Customer Solutions stakeholders to understand requirements and priorities.
• Recruit, develop, and manage a world class team of machine learning practitioners
• Contribute to a hiring process that attracts and retains world class technology talent who can push the envelope of natural language processing, machine learning, and network analysis.
• Stay on the frontier of AI and machine learning research and industry developments through an active role in thought leadership, research initiatives, industry working groups, and academic relationships.

About You

• Track record of success in demanding environments, especially with delivering ML enabled products and services in demanding and fast paced environments.
• Deep conceptual insight into how to apply ML algorithms and distill problems down to their essence.
• Strong product orientation and practical focus on delivering customer value and using techniques that deliver results; not getting stuck in academic beauty or theory.
• A hands-on leader who leads from the front, and is willing to help the team deliver.
• BS, MS, or PhD in Data Science, Computer Science, or related field.
• 10+ years of real-world professional experience building products based on Data Science & ML.
• Strong working knowledge of Knowledge Graphs, Entity Resolution, Natural Language Processing, Deep Learning, Classification and inference techniques, RLHF, PPO, multi-modal learning.
• Demonstrated experience leading a technical team and leveraging functional expertise to develop team members.
• Strong sense of shared ownership and a collaborative disposition.
• Strong written and verbal communication skills.

Nice to have, but not required

• You've worked with supply chain data, company data, or have familiarity with B2B economic modeling
• Multilingual skills

Technologies we love

• Languages: Python, SQL
• Tools: Tensorflow, XGBoost, Git, Kubernetes, Databricks, AWS, Azure
• Datastores: Postgres, DataBricks, ArangoDB