Associate Data Scientist – Customer Support

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.

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.