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A Senior Data Scientist I in the Finance Transformation team at CP Axtra is a hands-on expert who designs, develops, and deploys statistical models and machine learning algorithms to solve finance and commercial challenges across Makro and Lotus's, such as forecasting, margin and cost analytics, working-capital optimization, and fraud/anomaly detection. The role covers in-depth analysis, data preparation, building robust pipelines, and rigorously evaluating and optimizing model performance, while collaborating with Finance, engineering, and product teams and mentoring junior data scientists.
Responsibilities:
1.Design, develop, and implement statistical models and ML algorithms to solve finance and commercial problems (e.g., sales/cost forecasting, margin optimization, anomaly detection).
2.Conduct in-depth exploratory data analysis (EDA) to uncover trends, patterns, and actionable insights from large financial and transactional datasets.
3.Clean, transform, and validate data from Oracle Fusion and other sources to ensure data quality and integrity for modeling.
4.Build and maintain robust data pipelines and features for model training and inference.
5.Evaluate model performance using appropriate metrics, perform rigorous A/B testing, and continuously optimize models for production.
6.Collaborate with engineers, product owners, and Finance stakeholders to define requirements and integrate solutions.
7.Communicate complex analytical findings and model results clearly to both technical and non-technical finance audiences.
8.Research and apply cutting-edge data science techniques to improve existing methodologies and capabilities.
9.Develop and present data visualizations, dashboards, and reports to illustrate insights and track key financial metrics.
10.Mentor junior data scientists on best practices for analysis, modeling, and productionization.
Requirements
1. Expertise in developing and implementing complex machine learning and statistical models, ideally on financial or transactional data.
2. Proficient in preparing, cleaning, and transforming large datasets.
3. Strong coding skills in Python or R, with relevant libraries (e.g., scikit-learn, pandas, NumPy).
4. Ability to create clear, insightful data visualizations and dashboards for finance stakeholders.
5. Experience in designing, executing, and analyzing controlled experiments (A/B testing).
6. Excellent ability to articulate complex findings to technical and non-technical audiences and work cross-functionally.
7. Proficient in querying and managing data in relational and non-relational databases, including ERP sources such as Oracle Fusion.
Benefits