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- Software Engineer
- Key Responsibilities: -
- Model Development for Predictive Compliance Design and train machine learning models to detect anomalies, flag classification inconsistencies, forecast clearance delays, and assess customs risk.
- Hypothesis-Driven Analytics (Mode 2) Collaborate with product owners and GTCC advisors to define and test hypotheses that drive value (e.g., "Can we reduce customer audit exposure by 20% via automated HS classification?").
- Data Exploration & Feature Engineering Analyze customs, trade, and operational datasets to uncover patterns, engineer features, and refine model inputs across a diverse regulatory landscape.
- Insight Generation for Strategic Advisory Translate model outputs into insights that support dynamic duty optimization, risk management, and customer advisory—powering GTCC, CCT, and self-service dashboards.
- Algorithm Benchmarking & Validation Test multiple ML techniques (classification, time-series, clustering, etc.) and evaluate performance across regions, products, and trade flows.
- Collaborative Innovation Work as part of agile cross-functional squads with product managers, trade experts, and platform engineers to co-develop data products, but remain primarily focused on modeling and experimentation—not deployment.
- 5+ years of industry experience in data science or applied machine learning.
- Advanced knowledge in ML/algorithms and statistical modeling (classification, regression, clustering, anomaly detection).
- Proficient in Python, Jupyter, SQL, and libraries such as scikit-learn, pandas, XGBoost, TensorFlow, or PyTorch.
- Ability to design experiments, structure data science sprints, and communicate hypotheses and results.
- Experience with customs data, HS codes, FTAs, or trade compliance is highly valuable.
- Comfort working in ambiguity and iterating quickly with partial datasets.
- Strong storytelling skills—able to turn model outcomes into business-ready insights.
- Experience working in cloud environments such as Azure.
- Solid understanding of data pipelines and collaboration with data engineering teams.
- Model Accuracy: Improve classification precision and risk prediction through smarter, context-aware models.
- Innovation Velocity: Accelerate Mode 2 innovation by delivering validated use cases quarterly (e.g., HS classification, anomaly detection, quota risk).
- Insight-Driven Decisions: Enable GTCC and CCT to provide more precise, data-backed recommendations to high-value customers.
- Strategic Differentiation: Contribute to MCS’s goal of launching three new AI-powered products and achieving 99.9% compliance accuracy.
- MSc/PhD in Data Science, Statistics, Applied Math, or similar.
- 3–5+ years in hands-on model development (industry or academic research).
- Passionate about turning data into products that impact global trade, compliance, and operational excellence.
- Eager to work in a mission-driven team shaping the future of customs intelligence.
We are happy to support your need for any adjustments during the application and hiring process. If you need special assistance or an accommodation to use our website, apply for a position, or to perform a job, please contact us by emailing [email protected].
Key Skills
Ranked by relevance
ai
machine learning
storytelling
tensorflow
python
pandas
cloud
sql
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- Posted
- Aug 12, 2025
- Type
- Full-time
- Level
- Not Applicable
- Location
- Bangalore
- Company
- A.P. Moller - Maersk
Industries
Transportation
Logistics
Supply Chain
Storage
Categories
Engineering
Information Technology
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