Data Scientist

L'OREAL SINGAPORE PTE. LTD.; Singapore; On-site; SGD 80,000 - 110,000; Full time

Job summary

A leading cosmetics company in Singapore is seeking a seasoned data scientist to design and implement advanced forecasting models. You will drive strategic decision-making through data-driven insights across the SAPMENA region. The ideal candidate has over 5 years of experience in developing forecasting models, proficiency in Python and SQL, and familiarity with AI-ML technologies. This role offers an exciting opportunity to collaborate with diverse teams and contribute to business growth.

Qualifications

• 5+ years of experience developing and implementing forecasting models.
• Strong knowledge of time series analysis and regression analysis.
• Proficient in Python and SQL with relevant forecasting packages.

Responsibilities

• Lead design and maintenance of statistical forecasting models.
• Collaborate to translate business needs into data-driven solutions.
• Analyze large datasets to inform strategic decisions.

Skills

Statistical modeling

Data analysis

Machine learning algorithms

Time series analysis

Python programming

SQL

GitHub

Tools

Google Cloud Platform

XGBoost

CatBoost

LightGBM

Job description

Job Summary

Design, develop, and scale advanced data science and machine learning forecasting solutions across the SAPMENA region to drive strategic decision-making and business growth. Collaborate with cross-functional teams to deliver actionable insights and scalable AI-ML products that enhance forecast accuracy and operational efficiency.

Responsibilities

• Lead the design, development, implementation, and maintenance of sophisticated statistical forecasting models incorporating seasonality, promotions, media, traffic, and economic indicators to improve forecast accuracy.
• Collaborate with internal and external stakeholders including business units, data scientists, and product teams to translate business needs into actionable, data-driven solutions.
• Evaluate and compare forecasting model performance to recommend optimal approaches tailored to diverse business scenarios.
• Analyze large and complex datasets to identify patterns, insights, risks, and opportunities that inform strategic decisions.
• Communicate forecasting results and insights effectively to both technical and non-technical audiences through clear visualizations and presentations.
• Review MVP implementations to ensure adherence to Data Science best practices and provide recommendations for improvement.
• Stay current with advancements in forecasting techniques and technologies, proactively integrating improvements into models and processes.
• Contribute to building and maintaining robust data infrastructure for AI-ML solutions, ensuring data quality, accessibility, and scalability.
• Collaborate with data scientists and engineers to deploy scalable AI-ML solutions aligned with enterprise goals.
• Work proactively and independently to address product requirements and design optimal data science solutions within a matrix and multidisciplinary team environmentli>

Preferred competencies and qualifications

• 5+ years of experience developing and implementing forecasting models.
• Proven expertise in exploratory data analysis (EDA), data profiling, sampling, data engineering including data wrangling, storage, pipelines, and orchestration.
• Strong knowledge of time series analysis, regression analysis, and other statistical modeling techniques.
• Experience with machine learning algorithms such as ARIMA, Prophet, Random Forests, and Gradient Boosting algorithms (XGBoost, LightGBM, CatBoost).
• Proficiency in model explainability techniques including Shapley plots and data drift detection metrics.
• Advanced programming and analysis skills in Python and SQL, including experience with relevant forecasting packages.
• Prior experience with Data Science and ML Engineering on Google Cloud Platform.
• Proficiency in version control systems such as GitHub.
• Strong organizational skills and ability to collaborate effectively within matrix and multidisciplinary teams.
• Excellent communication and presentation skills, capable of explaining complex technical concepts to non-technical stakeholders.
• Experience in the Beauty or Retail/FMCG industry is advantageous.
• Experience handling large datasets exceeding 100 GB.
• Experience delivering AI-ML projects using Agile methodologies is preferred.