[ref. k53324901] Senior Data Scientist, Supply Chain - Geylang

apartmentLOUIS DREYFUS COMPANY ASIA PTE. LTD. placeGeylang descriptionPermanent calendar_month 

Overview / Brief

Louis Dreyfus Company is a leading merchant and processor of agricultural goods. Our activities span the entire value chain from farm to fork, across a broad range of business lines, we leverage our global reach and extensive asset network to serve our customers and consumers around the world.

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.

We are looking for a highly skilled Senior Data Scientist for our DT&A Platform with a strong background in Supply Chain. We seek for someone who enjoys hands-on data science work while also possess the ambition to lead strategic initiatives.
The role bridges data science, product management, and business strategy, playing a key role in shaping the future of our supply chain data ecosystem. A strong initial focus will involve tracking vessels and their cargoes while contribute to the creation of a digital twin of our operations.

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
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