Job Description
1. Lead the conceptualization and design of advanced modeling solutions (ML, Statistics or Mathematical) to tackle complex, large-scale Logistics challenges, ensuring alignment with business value and stakeholder needs.
2. Take ownership of developing, implementing, and automating robust data science models and pipelines, including feature generation, retraining, and prediction deployment, leveraging tools like BigQuery and Spark as needed.
3. Actively drive technical discussions and problem-solving sessions, contributing significant expertise and innovative ideas to overcome the toughest modeling hurdles alongside your Data Science peers and squad lead.
4. Translate sophisticated analytical findings and model outcomes into clear, actionable insights for stakeholders, demonstrably driving value and improvements in key business metrics.
5. Proactively engage with Data & ML Engineering and Tech teams to define critical data requirements and influence technical roadmaps, ensuring the necessary data infrastructure for impactful projects.
6. Make a significant impact within our fast-paced, global organization by delivering high-quality solutions, sharing knowledge, and contributing to the team's overall growth and best practices.
Qualifications
7. You have significant experience (ideally 5+ years) designing and implementing diverse machine learning models (, regression, classification, tree-based ensembles) to solve real-world business problems, backed by a strong theoretical foundation in statistics and probability.
8. You possess expert-level Python skills (incl. pandas, scikit-learn, etc.), proficiency in SQL, and demonstrable experience building robust, maintainable, and automated ML pipelines using Big Data technologies (, BigQuery, Spark) and workflow orchestration tools (, Airflow, Metaflow), applying software engineering best practices.
9. You excel at translating ambiguous business requirements into well-defined technical problems and data science solutions, critically evaluating assumptions and ensuring data quality throughout the process.
10. You are a strong communicator, capable of clearly explaining complex technical concepts, model intuition, and business implications to diverse audiences (both technical and non-technical stakeholders).
11. You are a proactive team player with proven experience collaborating effectively with peers and cross-functional teams (like Data Engineering and Tech) in a fast-paced, dynamic environment. Fluency in English is required.
Nice to have:
12. Deeper experience applying Operations Research techniques to solve optimization problems relevant to logistics.
13. Proven track record in designing, implementing, and analyzing complex experiments (beyond standard A/B tests) or applying causal inference methods.
14. Experience building interactive data visualizations, applications, or dashboards using libraries like Streamlit, Plotly Dash, or similar tools to communicate results effectively.