Product Manager, Data Science Platform (AI/ML)

Why project44?

At project44, we believe in better. We challenge the status quo because we know a better supply chain isn’t just possible—it’s essential. Better for our customers. Better for their business. Better for the world.

With our Decision Intelligence Platform, Movement, we’re redefining how global supply chains operate. By transforming fragmented logistics data into real-time, AI-powered insights, we empower companies to connect instantly, see clearly, act decisively, and automate intelligently. Our Supply Chain AI enhances visibility, drives smarter execution, and unlocks next-gen applications that keep businesses moving forward.
Headquartered in Chicago, IL with a 2nd HQ in Bengaluru, India we are powered by a diverse global team that is tackling the toughest logistics challenges with innovation, urgency, and purpose.

AI at project44

We expect every project44 team member, regardless of role or function, to actively leverage AI in their day-to-day work. Whether you're building product, serving customers, managing people, or running operations, AI is a tool you're expected to use with intent, curiosity, and judgment. We don't expect everyone to be a data scientist. We do expect everyone to be an intelligent user of AI: able to identify where it adds value, direct it effectively, evaluate outputs critically, and govern it responsibly. We invest in our team's AI fluency because we believe it's a competitive advantage for every person at project44, not just our engineers.

If you’re driven to solve meaningful problems, leverage AI to scale rapidly, drive impact daily, and be part of a high-performance team – we should talk.

In-office Commitment: Our office is where ideas spark, connections thrive, and innovation comes alive. We are looking for candidates who are enthusiastic and committed to joining our team on-site, in our beautiful headquarters four days a week. Together, we’re building something extraordinarily learn, grow, and thrive in our fast-paced, transformative environment.

We’re hiring a technical, hands-on Product Manager to scale ML-powered products (ETA, risk, anomalies/exceptions, network insights) while building Data Science as a Platform—reusable capabilities that accelerate model development, deployment, monitoring, and governance across multiple product areas. 

You’ll partner daily with Data Science, ML Engineering, Data Engineering, Platform Engineering, and Product teams to ship production ML and establish repeatable, measurable ML delivery. 

We expect every project44 team member, regardless of role or function, to actively leverage AI in their day-to-day work. Whether you're building product, serving customers, managing people, or running operations, AI is a tool you're expected to use with intent, curiosity, and judgment. We don't expect everyone to be a data scientist. We do expect everyone to be an intelligent user of AI: able to identify where it adds value, direct it effectively, evaluate outputs critically, and govern it responsibly. We invest in our team's AI fluency because we believe it's a competitive advantage for every person at project44, not just our engineers. 

Key Accountabilities

• Own the roadmap for applied ML capabilities beyond ETA (risk scoring, exception prediction, anomaly detection, carrier/network performance insights), from discovery to launch and iteration. 
• Define and deliver a DS/ML platform: feature management, experimentation, model registry, deployment patterns, monitoring/observability, governance, and self-serve tooling. 
• Translate customer workflows into ML problem statements: labels/targets, constraints, SLAs, interpretability, and “do no harm” launch gates. 
• Drive evaluation and experimentation: offline metrics/back testing, online testing (A/B, holdouts), and measurable business impact. 
• Partner with engineering on batch + real-time inference architectures, streaming/event-time feature needs, and reliability (SLOs, incident playbooks). 
• Establish and track platform success metrics: time-to-first-model, deployment frequency, reuse rate, model performance stability, incident rate, and ROI.

Minimum Qualifications

• 5–8+ years Product Management experience with 3–4+ years focused on DS/ML-driven products (or equivalent) 
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