Product Manager, Data Science Platform

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.    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.  
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.  
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  

• Familiarity with geospatial/event-time data, carrier APIs/EDI, entity resolution, and enterprise exception workflows  

• Platform product experience with internal “developer” customers and adoption metrics  

Diversity & Inclusion
We're designing the future of how the world moves and is connected through trade and global supply chains. We can only deliver a truly world-class product and experience if our teams are as diverse and unique communities we are building for. So it's up to us to create a company where anyone can bring their authentic self to work everyday. We're constantly working to improve, and we accept our responsibility to elevate the voices left in the margins. It's on every one of us.
Our focus on inclusion manifests in the way we hire, the customers we serve, and the regions we prioritize. We're building a company that every one of us at project44 is proud to work for: a company that celebrates you for being you.
We pride ourselves on celebrating everyone — project44 is an equal opportunity employer actively working on creating a diverse and inclusive work environment where underrepresented groups can thrive. If you share our values and our passion for helping the way the world moves, we’d love to review your application!
For any needed accommodations during the hiring process, please email [email protected]. Even if you don’t meet 100% of the above qualifications, you should still seriously consider applying. Studies show that you can still be considered for a role if you meet just 50% of the role’s requirements.