Senior Data Scientist I (Finance)

atCP Axtra PCL (Lotus's)

Senior Data Scientist I (Finance)

> CP Axtra

  • Bangkok, Thailand
  • Full-time

Workplace: on_site

Department: Technology

Description

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

  • International workplace
  • Opportunities for growth in e-commerce, wholesales, and retail industry
  • Competitive benefits
  • Fast-paced, dynamic, and supportive environment


Apply

[Apply at CP Axtra](https://apply.workable.com/joinmakropro/j/AA0E77E6C2/apply)

Experience required
  • any or no experience
Career level
  • Senior Level
Salary
  • Negotiable
Job function
  • IT / Programming
  • Finance
Job type
  • Full-time

Company overview

Size:2000-5000 employees
Industry:Retail
Location:Bangkok
Website:www.lotuss.com
Founded in:1994
Ranking:4/5

Lotus's operates in Thailand as an omni-channel retailer. It sets out to bring shoppers well-made products at reasonable prices, while contributing positively to customers, colleagues and communities.

Customers are reached through over 2,000 stores across Thailand and t ...

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Why join us:

“At Lotus's, we are looking for people who are the change-agent with a passion to grow in both work and life. People who have the ability to think in an agile way and make everyday as a history to leave their own legacy in every part of business.” Lotus's People are: People wh ...

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Head office: 629/1 Nawamintr Road, Nuanchan, Buengkoom, Bangkok 10230 , Thailand
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