Senior Data Scientist, Supply Chain - Toa Payoh

Overview / Brief

Structured as a matrix organization of six geographical regions and ten platforms, Louis Dreyfus Company is active in over 100 countries and employs approximately 18,000 people globally.

Diversity & Inclusion

LDC is driven by a set of shared values and high ethical standards

Diversity is part of our DNA. LDC strives to create a diverse and inclusive work environment where people can thrive regardless of gender, sexuality, ethnicity or background.

Sustainability

Sustainable value is at the heart of our purpose as a company

We are passionate about creating fair and sustainable value, both for our business and for other value chain stakeholders: our people, our business partners, the communities we touch and the environment around us.

The role offers an unparalleled opportunity to make a tangible impact on our global supply chain optimization and predictive capabilities.

Main Responsibilities:

• Data Product Development:

1. Design, develop, and manage the lifecycle of high-quality data products

• Algorithm Design:

1. Build advanced algorithms, with a focus on fuzzy matching, destination prediction, indicator modeling, and optimization within digital twins

• Data Management:

1. Collaborate with data engineers to handle complex, multi-format datasets, ensuring accurate analysis and effective data governance

• Team Coordination:

1. Work closely with cross-functional teams, including data architects, data engineers, and the product team to align on project goals, technical specifications, and deliverables

• Stakeholder Engagement:

1. Translate business needs into data-driven solutions, ensuring alignment with strategic goals

• Insights Presentation:

1. Synthesize raw data into actionable insights, delivering compelling visualizations and narratives for both technical and non-technical stakeholders on a regular basis

Experiences:

• At least 2-4 years of relevant experiences
• Strong background in AIS data, geographical data, or time series prediction
• Proven experience in designing and implementing quality algorithms for research and data analytics
• Experience in agricultural commodities trading, freight, logistics or similar markets is a strong plus
• Experience with modeling techniques and machine learning algorithms is a plus
• Passionate about staying abreast of the latest trends in AI, data science, and industry innovations
• Genuine interest in commodity trading industry
• Strong analytical and statistical capabilities, with a proven track record in problem-solving
• Excellent communication skills
• Ability to work independently and in collaborative settings
• Independent self-starter who takes initiative, and has a proactive attitude toward problems and issues
• Ability to present complex technical concepts in an accessible manner to stakeholders at all levels
• Ability to communicate with both technical and non-technical stakeholders

Technical Skills:

• Proficiency in Python and SQL
• Experience in data analysis libraries (e.g. Pandas, NumPy, SciPy)
• Experience in working with large, complex datasets
• Experience in implementing fuzzy matching algorithms, optimization techniques, and other advanced analytics methods are a strong plus

Academics:

• Degree or Master’s in Mathematics, Statistics, Econometrics, Computer Science, Data Science or related field of study