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)   Demonstrated ability shipping  end-to-end ML systems  to production and iterating based on outcomes   Strong technical fluency across the ML lifecycle (data → features → training → serving → monitoring → retraining)   Ability to operate between Sr and Principal: sets direction, aligns stakeholders, and drives execution across multiple teams   Excellent written communication (PRDs, decision docs) and crisp cross-functional leadership   In-office Commitment: Employees are expected to contribute to our collaborative culture by working in the office Four days weekly Technical skills (experience with many of the following)   SQL  (strong) and working knowledge of  Python  / notebooks / data analysis workflows   Data platforms:  Snowflake / BigQuery / Redshift / Databricks (Delta Lake)   Orchestration & ETL:  Airflow / Dagster / Prefect ,  dbt ,  Spark   Streaming/event systems:  Kafka / Kinesis / Flink   MLOps: experiment tracking/model registry ( MLflow / Weights & Biases ), pipelines ( Kubeflow / SageMaker Pipelines / TFX / Flyte/ Tensor flow ), serving ( SageMaker / Vertex AI / Databricks Model Serving / KServe / BentoML )   Feature stores:  Feast / Tecton /  SageMaker Feature Store   Monitoring/observability:  Arize / WhyLabs / Evidently  +  Prometheus/Grafana/Datadog   Platform fundamentals:  Docker/Kubernetes , API design ( REST/gRPC ), SLAs/SLOs, security &  PII  basics   LLMs/GenAI  (RAG, embeddings, vector DBs like Pinecone/Weaviate/Milvus), evaluation + guardrails   Preferred   Experience in  logistics / supply chain / transportation  or other high-volume operational domains   Fam