Senior Data Scientist I (Finance)

Head Office

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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

• Design, develop, and implement statistical models and ML algorithms to solve finance and commercial problems (e.g., sales/cost forecasting, margin optimization, anomaly detection).

• Conduct in-depth exploratory data analysis (EDA) to uncover trends, patterns, and actionable insights from large financial and transactional datasets.

• Clean, transform, and validate data from Oracle Fusion and other sources to ensure data quality and integrity for modeling.

• Build and maintain robust data pipelines and features for model training and inference.

• Evaluate model performance using appropriate metrics, perform rigorous A/B testing, and continuously optimize models for production.

• Collaborate with engineers, product owners, and Finance stakeholders to define requirements and integrate solutions.

• Communicate complex analytical findings and model results clearly to both technical and non-technical finance audiences.

• Research and apply cutting-edge data science techniques to improve existing methodologies and capabilities.

• Develop and present data visualizations, dashboards, and reports to illustrate insights and track key financial metrics.

• Mentor junior data scientists on best practices for analysis, modeling, and productionization.

Qualifications

• Expertise in developing and implementing complex machine learning and statistical models, ideally on financial or transactional data.

• Proficient in preparing, cleaning, and transforming large datasets.

• Strong coding skills in Python or R, with relevant libraries (e.g., scikit-learn, pandas, NumPy).

• Ability to create clear, insightful data visualizations and dashboards for finance stakeholders.

• Experience in designing, executing, and analyzing controlled experiments (A/B testing).

• Excellent ability to articulate complex findings to technical and non-technical audiences and work cross-functionally.

• Proficient in querying and managing data in relational and non-relational databases, including ERP sources such as Oracle Fusion.