Aera Technology is the Decision Intelligence company. We deliver innovation and services that enable enterprises to operate sustainably, intelligently, and efficiently. Our platform, Aera Decision Cloud™, integrates with your existing systems to digitize, augment, and automate decisions in real time. Aera helps enterprises around the world transform decision making – delivering millions of recommendations that have resulted in significant revenue gains and cost savings for some of the world’s best-known brands.
We’re looking for a customer-facing Associate Data Scientist who loves to debug, stress‑test, and “attack” models and data pipelines to uncover issues before customers do. You will be the bridge between deployed ML/AI solutions, customers, and internal teams—digging into data, finding root causes, and driving long-term fixes that make our solutions robust and trustworthy.
Responsibilities
Investigate complex and often disorganized datasets to diagnose underlying causes of issues such as model degradation, unexpected patterns, and data quality problems.
Perform extensive exploratory data analysis (EDA) to detect data drifts, anomalies, and quality issues that may impact model performance.
Design and run diagnostic experiments and adversarial tests to deliberately “break” models and solutions, revealing edge cases, failure modes, and hidden assumptions.
Define and implement validation checks, monitoring dashboards, and alerting mechanisms that surface issues early and guide triage.
Serve as the primary technical contact for data science issues, ensuring rapid responses, clear communication, and end-to-end ownership of problem resolution.
Fine-tune hyperparameters, retrain models, or implement minor algorithmic adjustments based on analytical insights.
Collaborate with support, product, engineering, and partner teams to implement comprehensive solutions, enhance processes, and ensure a positive customer experience.
Communicate technical findings clearly and empathetically to both customers and internal stakeholders, fostering trust through transparency and responsiveness.
Contribute to playbooks, runbooks, and best practices that continuously improve how we test, monitor, and support ML/AI solutions.
About You
Bachelor’s or Master’s degree in Engineering, Computer Science, Mathematics, Statistics, Data Science, or a related quantitative field; equivalent practical experience and demonstrated skills will also be considered.
1–3 years of experience in data science, data analysis, or technical support for data products; strong analytical interns or fresh graduates with outstanding debugging skills may also be considered.
Hands-on experience developing, deploying, and/or maintaining machine learning models in production environments.
Proficiency in Python, SQL, and relevant ML frameworks (e.g., scikit‑learn, TensorFlow, PyTorch).
Strong analytical and problem‑solving skills, with the ability to conduct rigorous data analysis and communicate findings clearly.
Demonstrated ability to work collaboratively in cross-functional teams and directly with customers to solve business problems.
Excellent communication skills, both written and verbal.
Domain experience in supply chain, logistics, or operations.
Experience with data visualization tools and monitoring/observability stacks.
